messages
listlengths 3
3
| metadata
dict |
|---|---|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following TOML to XML:\ntxn = \"e7d866e4-e217-4769-af91-6b199ac6c611\"\namount = 92.38\nstatus = \"completed\"\n[[audit_log]]\naction = \"created\"\nby = \"michaelmendez\"\ntimestamp = \"2016-05-22T16:08:01.325206\"\n\n[[audit_log]]\naction = \"created\"\nby = \"whitejoshua\"\ntimestamp = \"1980-02-24T13:33:42.943177\"\n\n[[audit_log]]\naction = \"created\"\nby = \"mollytaylor\"\ntimestamp = \"1971-07-22T05:19:29.270955\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.362521\"\nversion = \"v4.0\"\ntags = [ \"range\", \"cover\", \"use\", \"stand\", \"mean\",]\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<transaction_record>\n<txn>e7d866e4-e217-4769-af91-6b199ac6c611</txn>\n<amount>92.38</amount>\n<status>completed</status>\n<meta_info>\n<generated_at>2026-01-22T04:03:07.362521</generated_at>\n<version>v4.0</version>\n<tags>range</tags>\n<tags>cover</tags>\n<tags>use</tags>\n<tags>stand</tags>\n<tags>mean</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>michaelmendez</by>\n<timestamp>2016-05-22T16:08:01.325206</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>whitejoshua</by>\n<timestamp>1980-02-24T13:33:42.943177</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>mollytaylor</by>\n<timestamp>1971-07-22T05:19:29.270955</timestamp>\n</audit_log>\n</transaction_record>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "transaction_record",
"type": "conversion",
"prompt": "Convert the following TOML to XML:\ntxn = \"e7d866e4-e217-4769-af91-6b199ac6c611\"\namount = 92.38\nstatus = \"completed\"\n[[audit_log]]\naction = \"created\"\nby = \"michaelmendez\"\ntimestamp = \"2016-05-22T16:08:01.325206\"\n\n[[audit_log]]\naction = \"created\"\nby = \"whitejoshua\"\ntimestamp = \"1980-02-24T13:33:42.943177\"\n\n[[audit_log]]\naction = \"created\"\nby = \"mollytaylor\"\ntimestamp = \"1971-07-22T05:19:29.270955\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.362521\"\nversion = \"v4.0\"\ntags = [ \"range\", \"cover\", \"use\", \"stand\", \"mean\",]\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<transaction_record>\n<txn>e7d866e4-e217-4769-af91-6b199ac6c611</txn>\n<amount>92.38</amount>\n<status>completed</status>\n<meta_info>\n<generated_at>2026-01-22T04:03:07.362521</generated_at>\n<version>v4.0</version>\n<tags>range</tags>\n<tags>cover</tags>\n<tags>use</tags>\n<tags>stand</tags>\n<tags>mean</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>michaelmendez</by>\n<timestamp>2016-05-22T16:08:01.325206</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>whitejoshua</by>\n<timestamp>1980-02-24T13:33:42.943177</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>mollytaylor</by>\n<timestamp>1971-07-22T05:19:29.270955</timestamp>\n</audit_log>\n</transaction_record>",
"estimated_tokens": 329
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Reformat the CSV below into YAML:\nexperiment_id,title,metrics.accuracy,metrics.loss,metrics.epoch,config.batch_size,config.optimizer,config.lr\r\nEXP-548343,Analysis of special,0.9516,0.2734,49,64,sgd,0.001\r\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id: EXP-548343\ntitle: Analysis of special\nmetrics:\n accuracy: 0.9516\n loss: 0.2734\n epoch: 49\nconfig:\n batch_size: 64\n optimizer: sgd\n lr: 0.001\n"
}
] |
{
"format": "yaml",
"complexity": "simple",
"schema": "experiment_result",
"type": "conversion",
"prompt": "Reformat the CSV below into YAML:\nexperiment_id,title,metrics.accuracy,metrics.loss,metrics.epoch,config.batch_size,config.optimizer,config.lr\r\nEXP-548343,Analysis of special,0.9516,0.2734,49,64,sgd,0.001\r\n",
"output": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id: EXP-548343\ntitle: Analysis of special\nmetrics:\n accuracy: 0.9516\n loss: 0.2734\n epoch: 49\nconfig:\n batch_size: 64\n optimizer: sgd\n lr: 0.001\n",
"estimated_tokens": 186
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Convert the following TOML to JSON:\ncontract = \"cultivate cross-media markets\"\nparties = [ \"Cooper Group\", \"Lawrence Inc\",]\nsigned = false\n[[audit_log]]\naction = \"created\"\nby = \"daniel16\"\ntimestamp = \"2010-06-15T09:38:22.777743\"\n\n[[audit_log]]\naction = \"created\"\nby = \"wshaw\"\ntimestamp = \"2025-01-18T17:33:58.322335\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.351677\"\nversion = \"v1.0\"\ntags = [ \"could\", \"field\", \"interest\", \"between\", \"pressure\",]\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (contract, parties, signed...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"contract\": \"cultivate cross-media markets\",\n \"parties\": [\n \"Cooper Group\",\n \"Lawrence Inc\"\n ],\n \"signed\": false,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.351677\",\n \"version\": \"v1.0\",\n \"tags\": [\n \"could\",\n \"field\",\n \"interest\",\n \"between\",\n \"pressure\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"daniel16\",\n \"timestamp\": \"2010-06-15T09:38:22.777743\"\n },\n {\n \"action\": \"created\",\n \"by\": \"wshaw\",\n \"timestamp\": \"2025-01-18T17:33:58.322335\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "contract",
"type": "conversion",
"prompt": "Convert the following TOML to JSON:\ncontract = \"cultivate cross-media markets\"\nparties = [ \"Cooper Group\", \"Lawrence Inc\",]\nsigned = false\n[[audit_log]]\naction = \"created\"\nby = \"daniel16\"\ntimestamp = \"2010-06-15T09:38:22.777743\"\n\n[[audit_log]]\naction = \"created\"\nby = \"wshaw\"\ntimestamp = \"2025-01-18T17:33:58.322335\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.351677\"\nversion = \"v1.0\"\ntags = [ \"could\", \"field\", \"interest\", \"between\", \"pressure\",]\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (contract, parties, signed...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"contract\": \"cultivate cross-media markets\",\n \"parties\": [\n \"Cooper Group\",\n \"Lawrence Inc\"\n ],\n \"signed\": false,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.351677\",\n \"version\": \"v1.0\",\n \"tags\": [\n \"could\",\n \"field\",\n \"interest\",\n \"between\",\n \"pressure\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"daniel16\",\n \"timestamp\": \"2010-06-15T09:38:22.777743\"\n },\n {\n \"action\": \"created\",\n \"by\": \"wshaw\",\n \"timestamp\": \"2025-01-18T17:33:58.322335\"\n }\n ]\n}",
"estimated_tokens": 286
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Transform this data from XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>mcbridedennis</user>\n<rating>4</rating>\n<comment>Now through hospital one.</comment>\n</customer_review>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser,rating,comment\r\nmcbridedennis,4,Now through hospital one.\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "customer_review",
"type": "conversion",
"prompt": "Transform this data from XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>mcbridedennis</user>\n<rating>4</rating>\n<comment>Now through hospital one.</comment>\n</customer_review>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser,rating,comment\r\nmcbridedennis,4,Now through hospital one.\r\n",
"estimated_tokens": 163
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Generate social media post data in YAML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser: boyersylvia\npost: Interview knowledge ready hold establish hotel several. Money subject away without\n special. Oil whether short air become.\nlikes: 450\n"
}
] |
{
"format": "yaml",
"complexity": "simple",
"schema": "social_media_post",
"type": "generation",
"prompt": "Generate social media post data in YAML format.",
"output": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser: boyersylvia\npost: Interview knowledge ready hold establish hotel several. Money subject away without\n special. Oil whether short air become.\nlikes: 450\n",
"estimated_tokens": 176
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Generate customer review data in JSON format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"user\": \"eanthony\",\n \"rating\": 4,\n \"comment\": \"Wind through for son professional pull heart.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.271505\",\n \"version\": \"v5.0\",\n \"tags\": [\n \"population\",\n \"stay\",\n \"message\",\n \"management\",\n \"raise\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"lisa72\",\n \"timestamp\": \"1999-10-21T21:51:01.956523\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "customer_review",
"type": "generation",
"prompt": "Generate customer review data in JSON format.",
"output": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"user\": \"eanthony\",\n \"rating\": 4,\n \"comment\": \"Wind through for son professional pull heart.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.271505\",\n \"version\": \"v5.0\",\n \"tags\": [\n \"population\",\n \"stay\",\n \"message\",\n \"management\",\n \"raise\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"lisa72\",\n \"timestamp\": \"1999-10-21T21:51:01.956523\"\n }\n ]\n}",
"estimated_tokens": 246
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Create a CSV representation of lab result."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nid,test,value\r\n51f94fd4-dcd2-4c3e-8904-6ba0e2c5e14d,policy,55.370439795214644\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "lab_result",
"type": "generation",
"prompt": "Create a CSV representation of lab result.",
"output": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nid,test,value\r\n51f94fd4-dcd2-4c3e-8904-6ba0e2c5e14d,policy,55.370439795214644\r\n",
"estimated_tokens": 158
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Reformat the XML below into CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<financial_report>\n<company>Evans-Fisher</company>\n<revenue>721671</revenue>\n<profit>80335</profit>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.594892</generated_at>\n<version>v1.0</version>\n<tags>remember</tags>\n<tags>follow</tags>\n<tags>brother</tags>\n<tags>take</tags>\n<tags>quickly</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>anthonymoore</by>\n<timestamp>2025-11-01T14:47:27.012760</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>ohammond</by>\n<timestamp>2001-07-31T10:12:43.525046</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>mclaughlincassandra</by>\n<timestamp>2009-07-24T22:12:06.119047</timestamp>\n</audit_log>\n</financial_report>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (company, revenue, profit...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncompany,revenue,profit,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nEvans-Fisher,721671,80335,2026-01-22T04:03:05.594892,v1.0,\"[\"\"remember\"\", \"\"follow\"\", \"\"brother\"\", \"\"take\"\", \"\"quickly\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"anthonymoore\"\", \"\"timestamp\"\": \"\"2025-11-01T14:47:27.012760\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"ohammond\"\", \"\"timestamp\"\": \"\"2001-07-31T10:12:43.525046\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"mclaughlincassandra\"\", \"\"timestamp\"\": \"\"2009-07-24T22:12:06.119047\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "financial_report",
"type": "conversion",
"prompt": "Reformat the XML below into CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<financial_report>\n<company>Evans-Fisher</company>\n<revenue>721671</revenue>\n<profit>80335</profit>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.594892</generated_at>\n<version>v1.0</version>\n<tags>remember</tags>\n<tags>follow</tags>\n<tags>brother</tags>\n<tags>take</tags>\n<tags>quickly</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>anthonymoore</by>\n<timestamp>2025-11-01T14:47:27.012760</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>ohammond</by>\n<timestamp>2001-07-31T10:12:43.525046</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>mclaughlincassandra</by>\n<timestamp>2009-07-24T22:12:06.119047</timestamp>\n</audit_log>\n</financial_report>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (company, revenue, profit...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncompany,revenue,profit,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nEvans-Fisher,721671,80335,2026-01-22T04:03:05.594892,v1.0,\"[\"\"remember\"\", \"\"follow\"\", \"\"brother\"\", \"\"take\"\", \"\"quickly\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"anthonymoore\"\", \"\"timestamp\"\": \"\"2025-11-01T14:47:27.012760\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"ohammond\"\", \"\"timestamp\"\": \"\"2001-07-31T10:12:43.525046\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"mclaughlincassandra\"\", \"\"timestamp\"\": \"\"2009-07-24T22:12:06.119047\"\"}]\"\r\n",
"estimated_tokens": 278
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Reformat the JSON below into CSV:\n{\n \"endpoint\": \"/api/v1/users\",\n \"method\": \"GET\",\n \"responses\": {\n \"200\": \"OK\"\n }\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nendpoint,method,responses.200\r\n/api/v1/users,GET,OK\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "api_specification",
"type": "conversion",
"prompt": "Reformat the JSON below into CSV:\n{\n \"endpoint\": \"/api/v1/users\",\n \"method\": \"GET\",\n \"responses\": {\n \"200\": \"OK\"\n }\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nendpoint,method,responses.200\r\n/api/v1/users,GET,OK\r\n",
"estimated_tokens": 162
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Reformat the JSON below into CSV:\n{\n \"id\": \"96ae059c-406b-40c3-8fa5-aa9ecfd54725\",\n \"test\": \"service\",\n \"value\": 42.11838818121964,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:05.662055\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"ball\",\n \"thousand\",\n \"everybody\",\n \"whom\",\n \"performance\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"kenneth41\",\n \"timestamp\": \"1998-11-24T00:35:56.534669\"\n }\n ]\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (id, test, value...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nid,test,value,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\n96ae059c-406b-40c3-8fa5-aa9ecfd54725,service,42.11838818121964,2026-01-22T04:03:05.662055,v3.0,\"[\"\"ball\"\", \"\"thousand\"\", \"\"everybody\"\", \"\"whom\"\", \"\"performance\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"kenneth41\"\", \"\"timestamp\"\": \"\"1998-11-24T00:35:56.534669\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "lab_result",
"type": "conversion",
"prompt": "Reformat the JSON below into CSV:\n{\n \"id\": \"96ae059c-406b-40c3-8fa5-aa9ecfd54725\",\n \"test\": \"service\",\n \"value\": 42.11838818121964,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:05.662055\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"ball\",\n \"thousand\",\n \"everybody\",\n \"whom\",\n \"performance\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"kenneth41\",\n \"timestamp\": \"1998-11-24T00:35:56.534669\"\n }\n ]\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (id, test, value...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nid,test,value,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\n96ae059c-406b-40c3-8fa5-aa9ecfd54725,service,42.11838818121964,2026-01-22T04:03:05.662055,v3.0,\"[\"\"ball\"\", \"\"thousand\"\", \"\"everybody\"\", \"\"whom\"\", \"\"performance\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"kenneth41\"\", \"\"timestamp\"\": \"\"1998-11-24T00:35:56.534669\"\"}]\"\r\n",
"estimated_tokens": 233
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Transform this data from TOML to JSON:\ncourse = \"Adaptive transitional circuit\"\nweeks = 11\ncredits = 3\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"course\": \"Adaptive transitional circuit\",\n \"weeks\": 11,\n \"credits\": 3\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "course_syllabus",
"type": "conversion",
"prompt": "Transform this data from TOML to JSON:\ncourse = \"Adaptive transitional circuit\"\nweeks = 11\ncredits = 3\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"course\": \"Adaptive transitional circuit\",\n \"weeks\": 11,\n \"credits\": 3\n}",
"estimated_tokens": 163
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Convert the following XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<prescription>\n<rx>425345cd-6c7d-488c-9fac-6852b0fe978c</rx>\n<drug>opportunity</drug>\n<dosage>10mg</dosage>\n</prescription>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (rx, drug, dosage) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nrx,drug,dosage\r\n425345cd-6c7d-488c-9fac-6852b0fe978c,opportunity,10mg\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "prescription",
"type": "conversion",
"prompt": "Convert the following XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<prescription>\n<rx>425345cd-6c7d-488c-9fac-6852b0fe978c</rx>\n<drug>opportunity</drug>\n<dosage>10mg</dosage>\n</prescription>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (rx, drug, dosage) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nrx,drug,dosage\r\n425345cd-6c7d-488c-9fac-6852b0fe978c,opportunity,10mg\r\n",
"estimated_tokens": 163
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Output structured data for contract using JSON."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"contract\": \"morph real-time networks\",\n \"parties\": [\n \"Anderson Group\",\n \"Pitts PLC\"\n ],\n \"signed\": false\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "contract",
"type": "generation",
"prompt": "Output structured data for contract using JSON.",
"output": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"contract\": \"morph real-time networks\",\n \"parties\": [\n \"Anderson Group\",\n \"Pitts PLC\"\n ],\n \"signed\": false\n}",
"estimated_tokens": 166
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following TOML to XML:\nid = \"6b147962-18db-482c-997e-5db4699c3bf1\"\ntest = \"less\"\nvalue = 40.534189539121535\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<lab_result>\n<id>6b147962-18db-482c-997e-5db4699c3bf1</id>\n<test>less</test>\n<value>40.534189539121535</value>\n</lab_result>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "lab_result",
"type": "conversion",
"prompt": "Convert the following TOML to XML:\nid = \"6b147962-18db-482c-997e-5db4699c3bf1\"\ntest = \"less\"\nvalue = 40.534189539121535\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<lab_result>\n<id>6b147962-18db-482c-997e-5db4699c3bf1</id>\n<test>less</test>\n<value>40.534189539121535</value>\n</lab_result>",
"estimated_tokens": 183
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Convert the following YAML to CSV:\ntimestamp: '2026-01-22T04:03:04.971124'\nlevel: ERROR\nmessage: Suffer day soon range though book.\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntimestamp,level,message\r\n2026-01-22T04:03:04.971124,ERROR,Suffer day soon range though book.\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "error_log",
"type": "conversion",
"prompt": "Convert the following YAML to CSV:\ntimestamp: '2026-01-22T04:03:04.971124'\nlevel: ERROR\nmessage: Suffer day soon range though book.\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntimestamp,level,message\r\n2026-01-22T04:03:04.971124,ERROR,Suffer day soon range though book.\r\n",
"estimated_tokens": 171
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Convert the following XML to TOML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<experiment_result>\n<experiment_id>EXP-100053</experiment_id>\n<title>Analysis of hour</title>\n<metrics>\n<accuracy>0.791</accuracy>\n<loss>0.43</loss>\n<epoch>30</epoch>\n</metrics>\n<config>\n<batch_size>32</batch_size>\n<optimizer>sgd</optimizer>\n<lr>0.001</lr>\n</config>\n</experiment_result>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id = \"EXP-100053\"\ntitle = \"Analysis of hour\"\n\n[metrics]\naccuracy = 0.791\nloss = 0.43\nepoch = 30\n\n[config]\nbatch_size = 32\noptimizer = \"sgd\"\nlr = 0.001\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "experiment_result",
"type": "conversion",
"prompt": "Convert the following XML to TOML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<experiment_result>\n<experiment_id>EXP-100053</experiment_id>\n<title>Analysis of hour</title>\n<metrics>\n<accuracy>0.791</accuracy>\n<loss>0.43</loss>\n<epoch>30</epoch>\n</metrics>\n<config>\n<batch_size>32</batch_size>\n<optimizer>sgd</optimizer>\n<lr>0.001</lr>\n</config>\n</experiment_result>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id = \"EXP-100053\"\ntitle = \"Analysis of hour\"\n\n[metrics]\naccuracy = 0.791\nloss = 0.43\nepoch = 30\n\n[config]\nbatch_size = 32\noptimizer = \"sgd\"\nlr = 0.001\n",
"estimated_tokens": 184
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Create a XML representation of api specification."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 5 root fields (endpoint, method, responses...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<api_specification>\n<endpoint>/api/v1/users</endpoint>\n<method>GET</method>\n<responses>\n<_200>OK</_200>\n</responses>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.690335</generated_at>\n<version>v4.0</version>\n<tags>base</tags>\n<tags>main</tags>\n<tags>never</tags>\n<tags>manage</tags>\n<tags>test</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>crobinson</by>\n<timestamp>1995-03-16T22:55:32.772544</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>gary86</by>\n<timestamp>1999-08-03T03:28:33.243961</timestamp>\n</audit_log>\n</api_specification>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "api_specification",
"type": "generation",
"prompt": "Create a XML representation of api specification.",
"output": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 5 root fields (endpoint, method, responses...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<api_specification>\n<endpoint>/api/v1/users</endpoint>\n<method>GET</method>\n<responses>\n<_200>OK</_200>\n</responses>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.690335</generated_at>\n<version>v4.0</version>\n<tags>base</tags>\n<tags>main</tags>\n<tags>never</tags>\n<tags>manage</tags>\n<tags>test</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>crobinson</by>\n<timestamp>1995-03-16T22:55:32.772544</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>gary86</by>\n<timestamp>1999-08-03T03:28:33.243961</timestamp>\n</audit_log>\n</api_specification>",
"estimated_tokens": 293
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Output structured data for news_article using JSON."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"headline\": \"Republican respond individual town east.\",\n \"body\": \"Appear religious Republican member from store. Store note benefit spring ask key energy. House identify back.\\nMy seek suggest care movement anyone. Difference control perform good.\",\n \"author\": \"Tommy Porter\"\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "news_article",
"type": "generation",
"prompt": "Output structured data for news_article using JSON.",
"output": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"headline\": \"Republican respond individual town east.\",\n \"body\": \"Appear religious Republican member from store. Store note benefit spring ask key energy. House identify back.\\nMy seek suggest care movement anyone. Difference control perform good.\",\n \"author\": \"Tommy Porter\"\n}",
"estimated_tokens": 207
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Reformat the YAML below into TOML:\nstudent: Joshua Gill\nscore: 35\ngrade: A\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nstudent = \"Joshua Gill\"\nscore = 35\ngrade = \"A\"\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "student_assessment",
"type": "conversion",
"prompt": "Reformat the YAML below into TOML:\nstudent: Joshua Gill\nscore: 35\ngrade: A\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nstudent = \"Joshua Gill\"\nscore = 35\ngrade = \"A\"\n",
"estimated_tokens": 152
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Generate course syllabus data in JSON format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 5 root fields (course, weeks, credits...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"course\": \"Polarized fresh-thinking framework\",\n \"weeks\": 11,\n \"credits\": 3,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:05.143414\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"job\",\n \"professional\",\n \"price\",\n \"once\",\n \"offer\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"tracey70\",\n \"timestamp\": \"2008-06-05T04:53:27.174089\"\n },\n {\n \"action\": \"created\",\n \"by\": \"jeffery54\",\n \"timestamp\": \"1984-12-14T02:13:43.404848\"\n },\n {\n \"action\": \"created\",\n \"by\": \"eross\",\n \"timestamp\": \"2014-01-16T14:33:28.535750\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "course_syllabus",
"type": "generation",
"prompt": "Generate course syllabus data in JSON format.",
"output": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 5 root fields (course, weeks, credits...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"course\": \"Polarized fresh-thinking framework\",\n \"weeks\": 11,\n \"credits\": 3,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:05.143414\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"job\",\n \"professional\",\n \"price\",\n \"once\",\n \"offer\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"tracey70\",\n \"timestamp\": \"2008-06-05T04:53:27.174089\"\n },\n {\n \"action\": \"created\",\n \"by\": \"jeffery54\",\n \"timestamp\": \"1984-12-14T02:13:43.404848\"\n },\n {\n \"action\": \"created\",\n \"by\": \"eross\",\n \"timestamp\": \"2014-01-16T14:33:28.535750\"\n }\n ]\n}",
"estimated_tokens": 296
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Convert the following CSV to YAML:\nexperiment_id,title,metrics.accuracy,metrics.loss,metrics.epoch,config.batch_size,config.optimizer,config.lr\r\nEXP-880755,Analysis of project,0.7685,0.4944,84,64,adam,0.001\r\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id: EXP-880755\ntitle: Analysis of project\nmetrics:\n accuracy: 0.7685\n loss: 0.4944\n epoch: 84\nconfig:\n batch_size: 64\n optimizer: adam\n lr: 0.001\n"
}
] |
{
"format": "yaml",
"complexity": "medium",
"schema": "experiment_result",
"type": "conversion",
"prompt": "Convert the following CSV to YAML:\nexperiment_id,title,metrics.accuracy,metrics.loss,metrics.epoch,config.batch_size,config.optimizer,config.lr\r\nEXP-880755,Analysis of project,0.7685,0.4944,84,64,adam,0.001\r\n",
"output": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id: EXP-880755\ntitle: Analysis of project\nmetrics:\n accuracy: 0.7685\n loss: 0.4944\n epoch: 84\nconfig:\n batch_size: 64\n optimizer: adam\n lr: 0.001\n",
"estimated_tokens": 186
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Create a YAML representation of customer review."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser: lori80\nrating: 4\ncomment: Direction sign week represent thing friend art.\nmeta_info:\n generated_at: '2026-01-22T04:03:05.005015'\n version: v5.0\n tags:\n - successful\n - every\n - still\n - unit\n - score\naudit_log:\n- action: created\n by: fpowell\n timestamp: '2024-12-06T01:40:04.096854'\n- action: created\n by: kimberly73\n timestamp: '1986-01-28T21:51:25.896323'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "customer_review",
"type": "generation",
"prompt": "Create a YAML representation of customer review.",
"output": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser: lori80\nrating: 4\ncomment: Direction sign week represent thing friend art.\nmeta_info:\n generated_at: '2026-01-22T04:03:05.005015'\n version: v5.0\n tags:\n - successful\n - every\n - still\n - unit\n - score\naudit_log:\n- action: created\n by: fpowell\n timestamp: '2024-12-06T01:40:04.096854'\n- action: created\n by: kimberly73\n timestamp: '1986-01-28T21:51:25.896323'\n",
"estimated_tokens": 232
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Create a YAML representation of experiment result."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The experiment_result should contain a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nexperiment_id: EXP-481272\ntitle: Analysis of production\nmetrics:\n accuracy: 0.9889\n loss: 0.3569\n epoch: 46\nconfig:\n batch_size: 128\n optimizer: adam\n lr: 0.001\n"
}
] |
{
"format": "yaml",
"complexity": "simple",
"schema": "experiment_result",
"type": "generation",
"prompt": "Create a YAML representation of experiment result.",
"output": "Approach:\n1. Define the schema: The experiment_result should contain a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nexperiment_id: EXP-481272\ntitle: Analysis of production\nmetrics:\n accuracy: 0.9889\n loss: 0.3569\n epoch: 46\nconfig:\n batch_size: 128\n optimizer: adam\n lr: 0.001\n",
"estimated_tokens": 182
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Convert the following JSON to TOML:\n{\n \"experiment_id\": \"EXP-481272\",\n \"title\": \"Analysis of production\",\n \"metrics\": {\n \"accuracy\": 0.9889,\n \"loss\": 0.3569,\n \"epoch\": 46\n },\n \"config\": {\n \"batch_size\": 128,\n \"optimizer\": \"adam\",\n \"lr\": 0.001\n }\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id = \"EXP-481272\"\ntitle = \"Analysis of production\"\n\n[metrics]\naccuracy = 0.9889\nloss = 0.3569\nepoch = 46\n\n[config]\nbatch_size = 128\noptimizer = \"adam\"\nlr = 0.001\n"
}
] |
{
"format": "toml",
"complexity": "simple",
"schema": "experiment_result",
"type": "conversion",
"prompt": "Convert the following JSON to TOML:\n{\n \"experiment_id\": \"EXP-481272\",\n \"title\": \"Analysis of production\",\n \"metrics\": {\n \"accuracy\": 0.9889,\n \"loss\": 0.3569,\n \"epoch\": 46\n },\n \"config\": {\n \"batch_size\": 128,\n \"optimizer\": \"adam\",\n \"lr\": 0.001\n }\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id = \"EXP-481272\"\ntitle = \"Analysis of production\"\n\n[metrics]\naccuracy = 0.9889\nloss = 0.3569\nepoch = 46\n\n[config]\nbatch_size = 128\noptimizer = \"adam\"\nlr = 0.001\n",
"estimated_tokens": 187
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Reformat the TOML below into YAML:\nheadline = \"Involve these meet generation fight.\"\nbody = \"Community human either market all body direction. Different miss space maybe. Bar daughter institution as. Woman serve discuss industry.\\nAnimal item or across guess forward.\"\nauthor = \"Nicole Walker\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nheadline: Involve these meet generation fight.\nbody: 'Community human either market all body direction. Different miss space maybe.\n Bar daughter institution as. Woman serve discuss industry.\n\n Animal item or across guess forward.'\nauthor: Nicole Walker\n"
}
] |
{
"format": "yaml",
"complexity": "simple",
"schema": "news_article",
"type": "conversion",
"prompt": "Reformat the TOML below into YAML:\nheadline = \"Involve these meet generation fight.\"\nbody = \"Community human either market all body direction. Different miss space maybe. Bar daughter institution as. Woman serve discuss industry.\\nAnimal item or across guess forward.\"\nauthor = \"Nicole Walker\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nheadline: Involve these meet generation fight.\nbody: 'Community human either market all body direction. Different miss space maybe.\n Bar daughter institution as. Woman serve discuss industry.\n\n Animal item or across guess forward.'\nauthor: Nicole Walker\n",
"estimated_tokens": 207
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Create a YAML representation of transaction record."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ntxn: a7c2ec3a-958e-4d8a-a31a-0a31d026b509\namount: 212.62\nstatus: completed\n"
}
] |
{
"format": "yaml",
"complexity": "medium",
"schema": "transaction_record",
"type": "generation",
"prompt": "Create a YAML representation of transaction record.",
"output": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ntxn: a7c2ec3a-958e-4d8a-a31a-0a31d026b509\namount: 212.62\nstatus: completed\n",
"estimated_tokens": 156
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Reformat the TOML below into CSV:\ntxn = \"a7c2ec3a-958e-4d8a-a31a-0a31d026b509\"\namount = 212.62\nstatus = \"completed\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntxn,amount,status\r\na7c2ec3a-958e-4d8a-a31a-0a31d026b509,212.62,completed\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "transaction_record",
"type": "conversion",
"prompt": "Reformat the TOML below into CSV:\ntxn = \"a7c2ec3a-958e-4d8a-a31a-0a31d026b509\"\namount = 212.62\nstatus = \"completed\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntxn,amount,status\r\na7c2ec3a-958e-4d8a-a31a-0a31d026b509,212.62,completed\r\n",
"estimated_tokens": 165
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Create a TOML representation of research paper."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The research_paper should contain a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\npaper_id = \"arXiv:2021.79243\"\ntitle = \"Configurable bandwidth-monitored protocol\"\nabstract = \"This billion number Congress. Account suddenly detail short.\\nNational executive cause soldier Mr left home. Each rather management international full. Save very soldier beat kid tonight.\"\nkeywords = [ \"street\", \"mission\", \"involve\", \"with\", \"must\",]\n[[authors]]\nname = \"Paula Nelson\"\naffiliation = \"Underwood-Kemp\"\nemail = \"kristacaldwell@example.com\"\n\n[[authors]]\nname = \"James Palmer\"\naffiliation = \"Mccoy Group\"\nemail = \"smeyer@example.com\"\n\n[[authors]]\nname = \"Dr. Douglas Clarke\"\naffiliation = \"Gonzalez-Martinez\"\nemail = \"christine78@example.com\"\n\n[[authors]]\nname = \"Linda Olson\"\naffiliation = \"James LLC\"\nemail = \"andrea59@example.org\"\n\n[publication]\nvenue = \"NeurIPS\"\nyear = 2020\ndoi = \"10.5005/HLeh\"\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "research_paper",
"type": "generation",
"prompt": "Create a TOML representation of research paper.",
"output": "Approach:\n1. Define the schema: The research_paper should contain a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\npaper_id = \"arXiv:2021.79243\"\ntitle = \"Configurable bandwidth-monitored protocol\"\nabstract = \"This billion number Congress. Account suddenly detail short.\\nNational executive cause soldier Mr left home. Each rather management international full. Save very soldier beat kid tonight.\"\nkeywords = [ \"street\", \"mission\", \"involve\", \"with\", \"must\",]\n[[authors]]\nname = \"Paula Nelson\"\naffiliation = \"Underwood-Kemp\"\nemail = \"kristacaldwell@example.com\"\n\n[[authors]]\nname = \"James Palmer\"\naffiliation = \"Mccoy Group\"\nemail = \"smeyer@example.com\"\n\n[[authors]]\nname = \"Dr. Douglas Clarke\"\naffiliation = \"Gonzalez-Martinez\"\nemail = \"christine78@example.com\"\n\n[[authors]]\nname = \"Linda Olson\"\naffiliation = \"James LLC\"\nemail = \"andrea59@example.org\"\n\n[publication]\nvenue = \"NeurIPS\"\nyear = 2020\ndoi = \"10.5005/HLeh\"\n",
"estimated_tokens": 337
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Create a CSV representation of student assessment."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The student_assessment should contain a dictionary with 5 root fields (student, score, grade...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nstudent,score,grade,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nZachary Brewer,97,C,2026-01-22T04:03:05.249070,v5.0,\"[\"\"me\"\", \"\"deep\"\", \"\"technology\"\", \"\"million\"\", \"\"behind\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"matthewsantos\"\", \"\"timestamp\"\": \"\"1973-04-05T10:03:19.246516\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "student_assessment",
"type": "generation",
"prompt": "Create a CSV representation of student assessment.",
"output": "Approach:\n1. Define the schema: The student_assessment should contain a dictionary with 5 root fields (student, score, grade...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nstudent,score,grade,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nZachary Brewer,97,C,2026-01-22T04:03:05.249070,v5.0,\"[\"\"me\"\", \"\"deep\"\", \"\"technology\"\", \"\"million\"\", \"\"behind\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"matthewsantos\"\", \"\"timestamp\"\": \"\"1973-04-05T10:03:19.246516\"\"}]\"\r\n",
"estimated_tokens": 219
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Transform this data from YAML to TOML:\ncontract: morph real-time networks\nparties:\n- Anderson Group\n- Pitts PLC\nsigned: false\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncontract = \"morph real-time networks\"\nparties = [ \"Anderson Group\", \"Pitts PLC\",]\nsigned = false\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "contract",
"type": "conversion",
"prompt": "Transform this data from YAML to TOML:\ncontract: morph real-time networks\nparties:\n- Anderson Group\n- Pitts PLC\nsigned: false\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncontract = \"morph real-time networks\"\nparties = [ \"Anderson Group\", \"Pitts PLC\",]\nsigned = false\n",
"estimated_tokens": 166
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Generate customer review data in CSV format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser,rating,comment\r\ngarciashelly,3,Commercial wall factor Congress.\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "customer_review",
"type": "generation",
"prompt": "Generate customer review data in CSV format.",
"output": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser,rating,comment\r\ngarciashelly,3,Commercial wall factor Congress.\r\n",
"estimated_tokens": 158
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Generate customer review data in XML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>pamela79</user>\n<rating>5</rating>\n<comment>Congress interest employee such real sea.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.702005</generated_at>\n<version>v3.0</version>\n<tags>card</tags>\n<tags>model</tags>\n<tags>skill</tags>\n<tags>southern</tags>\n<tags>summer</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>leejohn</by>\n<timestamp>2009-12-30T14:04:14.639958</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>swilkerson</by>\n<timestamp>2002-06-01T00:16:21.688092</timestamp>\n</audit_log>\n</customer_review>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "customer_review",
"type": "generation",
"prompt": "Generate customer review data in XML format.",
"output": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>pamela79</user>\n<rating>5</rating>\n<comment>Congress interest employee such real sea.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.702005</generated_at>\n<version>v3.0</version>\n<tags>card</tags>\n<tags>model</tags>\n<tags>skill</tags>\n<tags>southern</tags>\n<tags>summer</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>leejohn</by>\n<timestamp>2009-12-30T14:04:14.639958</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>swilkerson</by>\n<timestamp>2002-06-01T00:16:21.688092</timestamp>\n</audit_log>\n</customer_review>",
"estimated_tokens": 293
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Reformat the YAML below into TOML:\nexperiment_id: EXP-616884\ntitle: Analysis of and\nmetrics:\n accuracy: 0.7673\n loss: 0.4367\n epoch: 22\nconfig:\n batch_size: 32\n optimizer: sgd\n lr: 0.001\nmeta_info:\n generated_at: '2026-01-22T04:03:05.730891'\n version: v4.0\n tags:\n - suddenly\n - western\n - well\n - ahead\n - director\naudit_log:\n- action: created\n by: thomasmarvin\n timestamp: '2007-02-20T21:53:12.454337'\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 6 root fields (experiment_id, title, metrics...) and a nesting depth of 3.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id = \"EXP-616884\"\ntitle = \"Analysis of and\"\n[[audit_log]]\naction = \"created\"\nby = \"thomasmarvin\"\ntimestamp = \"2007-02-20T21:53:12.454337\"\n\n[metrics]\naccuracy = 0.7673\nloss = 0.4367\nepoch = 22\n\n[config]\nbatch_size = 32\noptimizer = \"sgd\"\nlr = 0.001\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.730891\"\nversion = \"v4.0\"\ntags = [ \"suddenly\", \"western\", \"well\", \"ahead\", \"director\",]\n"
}
] |
{
"format": "toml",
"complexity": "complex",
"schema": "experiment_result",
"type": "conversion",
"prompt": "Reformat the YAML below into TOML:\nexperiment_id: EXP-616884\ntitle: Analysis of and\nmetrics:\n accuracy: 0.7673\n loss: 0.4367\n epoch: 22\nconfig:\n batch_size: 32\n optimizer: sgd\n lr: 0.001\nmeta_info:\n generated_at: '2026-01-22T04:03:05.730891'\n version: v4.0\n tags:\n - suddenly\n - western\n - well\n - ahead\n - director\naudit_log:\n- action: created\n by: thomasmarvin\n timestamp: '2007-02-20T21:53:12.454337'\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 6 root fields (experiment_id, title, metrics...) and a nesting depth of 3.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nexperiment_id = \"EXP-616884\"\ntitle = \"Analysis of and\"\n[[audit_log]]\naction = \"created\"\nby = \"thomasmarvin\"\ntimestamp = \"2007-02-20T21:53:12.454337\"\n\n[metrics]\naccuracy = 0.7673\nloss = 0.4367\nepoch = 22\n\n[config]\nbatch_size = 32\noptimizer = \"sgd\"\nlr = 0.001\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.730891\"\nversion = \"v4.0\"\ntags = [ \"suddenly\", \"western\", \"well\", \"ahead\", \"director\",]\n",
"estimated_tokens": 242
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Generate research paper data in CSV format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The research_paper should contain a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\npaper_id,title,authors,abstract,keywords,publication.venue,publication.year,publication.doi\r\narXiv:2020.70770,Stand-alone needs-based standardization,\"[{\"\"name\"\": \"\"Michael Deleon\"\", \"\"affiliation\"\": \"\"Thomas Inc\"\", \"\"email\"\": \"\"richard73@example.com\"\"}, {\"\"name\"\": \"\"Laurie Torres\"\", \"\"affiliation\"\": \"\"Gross Ltd\"\", \"\"email\"\": \"\"zunigawendy@example.org\"\"}, {\"\"name\"\": \"\"Jasmin Mcdonald\"\", \"\"affiliation\"\": \"\"Obrien-Day\"\", \"\"email\"\": \"\"stacie24@example.com\"\"}]\",\"Policy someone thank company book. Once same nation charge every.\nStudent game by event.\",\"[\"\"say\"\", \"\"adult\"\", \"\"other\"\", \"\"yet\"\"]\",Nature,2024,10.7430/lhxI\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "research_paper",
"type": "generation",
"prompt": "Generate research paper data in CSV format.",
"output": "Approach:\n1. Define the schema: The research_paper should contain a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\npaper_id,title,authors,abstract,keywords,publication.venue,publication.year,publication.doi\r\narXiv:2020.70770,Stand-alone needs-based standardization,\"[{\"\"name\"\": \"\"Michael Deleon\"\", \"\"affiliation\"\": \"\"Thomas Inc\"\", \"\"email\"\": \"\"richard73@example.com\"\"}, {\"\"name\"\": \"\"Laurie Torres\"\", \"\"affiliation\"\": \"\"Gross Ltd\"\", \"\"email\"\": \"\"zunigawendy@example.org\"\"}, {\"\"name\"\": \"\"Jasmin Mcdonald\"\", \"\"affiliation\"\": \"\"Obrien-Day\"\", \"\"email\"\": \"\"stacie24@example.com\"\"}]\",\"Policy someone thank company book. Once same nation charge every.\nStudent game by event.\",\"[\"\"say\"\", \"\"adult\"\", \"\"other\"\", \"\"yet\"\"]\",Nature,2024,10.7430/lhxI\r\n",
"estimated_tokens": 298
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Create a TOML representation of product listing."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct = \"over\"\nprice = 34.06\nstock = 26\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "product_listing",
"type": "generation",
"prompt": "Create a TOML representation of product listing.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct = \"over\"\nprice = 34.06\nstock = 26\n",
"estimated_tokens": 145
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Transform this data from TOML to JSON:\nheadline = \"Yet poor evidence environment general.\"\nbody = \"Poor worker recently factor form sure argue. Long start according sense story. Share Congress sometimes tough green when image.\"\nauthor = \"James Morales\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"headline\": \"Yet poor evidence environment general.\",\n \"body\": \"Poor worker recently factor form sure argue. Long start according sense story. Share Congress sometimes tough green when image.\",\n \"author\": \"James Morales\"\n}"
}
] |
{
"format": "json",
"complexity": "simple",
"schema": "news_article",
"type": "conversion",
"prompt": "Transform this data from TOML to JSON:\nheadline = \"Yet poor evidence environment general.\"\nbody = \"Poor worker recently factor form sure argue. Long start according sense story. Share Congress sometimes tough green when image.\"\nauthor = \"James Morales\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"headline\": \"Yet poor evidence environment general.\",\n \"body\": \"Poor worker recently factor form sure argue. Long start according sense story. Share Congress sometimes tough green when image.\",\n \"author\": \"James Morales\"\n}",
"estimated_tokens": 200
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Reformat the TOML below into XML:\nid = \"0d0bfcdd-43a6-4734-a3a3-2e84ac619a8e\"\ntest = \"health\"\nvalue = 22.736645656882736\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<lab_result>\n<id>0d0bfcdd-43a6-4734-a3a3-2e84ac619a8e</id>\n<test>health</test>\n<value>22.736645656882736</value>\n</lab_result>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "lab_result",
"type": "conversion",
"prompt": "Reformat the TOML below into XML:\nid = \"0d0bfcdd-43a6-4734-a3a3-2e84ac619a8e\"\ntest = \"health\"\nvalue = 22.736645656882736\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<lab_result>\n<id>0d0bfcdd-43a6-4734-a3a3-2e84ac619a8e</id>\n<test>health</test>\n<value>22.736645656882736</value>\n</lab_result>",
"estimated_tokens": 184
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Convert the following TOML to CSV:\ntxn = \"ba8535a3-b2c3-4f3f-91cb-80968767d87b\"\namount = 415.52\nstatus = \"completed\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntxn,amount,status\r\nba8535a3-b2c3-4f3f-91cb-80968767d87b,415.52,completed\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "transaction_record",
"type": "conversion",
"prompt": "Convert the following TOML to CSV:\ntxn = \"ba8535a3-b2c3-4f3f-91cb-80968767d87b\"\namount = 415.52\nstatus = \"completed\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntxn,amount,status\r\nba8535a3-b2c3-4f3f-91cb-80968767d87b,415.52,completed\r\n",
"estimated_tokens": 165
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Convert the following TOML to YAML:\nuser = \"alisonhancock\"\npost = \"Determine attention certainly relate case drug. Everything science fall war.\"\nlikes = 598\n[[audit_log]]\naction = \"created\"\nby = \"dgrant\"\ntimestamp = \"1972-01-31T14:11:50.299557\"\n\n[[audit_log]]\naction = \"created\"\nby = \"ymedina\"\ntimestamp = \"1984-06-17T07:31:52.838713\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.945233\"\nversion = \"v5.0\"\ntags = [ \"outside\", \"benefit\", \"drug\", \"professor\", \"responsibility\",]\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser: alisonhancock\npost: Determine attention certainly relate case drug. Everything science fall war.\nlikes: 598\nmeta_info:\n generated_at: '2026-01-22T04:03:05.945233'\n version: v5.0\n tags:\n - outside\n - benefit\n - drug\n - professor\n - responsibility\naudit_log:\n- action: created\n by: dgrant\n timestamp: '1972-01-31T14:11:50.299557'\n- action: created\n by: ymedina\n timestamp: '1984-06-17T07:31:52.838713'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "social_media_post",
"type": "conversion",
"prompt": "Convert the following TOML to YAML:\nuser = \"alisonhancock\"\npost = \"Determine attention certainly relate case drug. Everything science fall war.\"\nlikes = 598\n[[audit_log]]\naction = \"created\"\nby = \"dgrant\"\ntimestamp = \"1972-01-31T14:11:50.299557\"\n\n[[audit_log]]\naction = \"created\"\nby = \"ymedina\"\ntimestamp = \"1984-06-17T07:31:52.838713\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.945233\"\nversion = \"v5.0\"\ntags = [ \"outside\", \"benefit\", \"drug\", \"professor\", \"responsibility\",]\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser: alisonhancock\npost: Determine attention certainly relate case drug. Everything science fall war.\nlikes: 598\nmeta_info:\n generated_at: '2026-01-22T04:03:05.945233'\n version: v5.0\n tags:\n - outside\n - benefit\n - drug\n - professor\n - responsibility\naudit_log:\n- action: created\n by: dgrant\n timestamp: '1972-01-31T14:11:50.299557'\n- action: created\n by: ymedina\n timestamp: '1984-06-17T07:31:52.838713'\n",
"estimated_tokens": 247
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Create a JSON representation of lab result."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"id\": \"6b147962-18db-482c-997e-5db4699c3bf1\",\n \"test\": \"less\",\n \"value\": 40.534189539121535\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "lab_result",
"type": "generation",
"prompt": "Create a JSON representation of lab result.",
"output": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"id\": \"6b147962-18db-482c-997e-5db4699c3bf1\",\n \"test\": \"less\",\n \"value\": 40.534189539121535\n}",
"estimated_tokens": 159
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Output structured data for lab_result using CSV."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nid,test,value\r\n6b147962-18db-482c-997e-5db4699c3bf1,less,40.534189539121535\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "lab_result",
"type": "generation",
"prompt": "Output structured data for lab_result using CSV.",
"output": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nid,test,value\r\n6b147962-18db-482c-997e-5db4699c3bf1,less,40.534189539121535\r\n",
"estimated_tokens": 157
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Convert the following XML to YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<sales_analytics>\n<period>Q1</period>\n<sales>1293</sales>\n<region>East Luke</region>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.493282</generated_at>\n<version>v3.0</version>\n<tags>always</tags>\n<tags>someone</tags>\n<tags>guy</tags>\n<tags>financial</tags>\n<tags>thought</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>warrenlauren</by>\n<timestamp>1982-02-19T17:59:18.620684</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>robertblackburn</by>\n<timestamp>1976-03-29T15:21:16.808589</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>csuarez</by>\n<timestamp>2013-08-27T14:23:21.257692</timestamp>\n</audit_log>\n</sales_analytics>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (period, sales, region...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nperiod: Q1\nsales: 1293\nregion: East Luke\nmeta_info:\n generated_at: '2026-01-22T04:03:06.493282'\n version: v3.0\n tags:\n - always\n - someone\n - guy\n - financial\n - thought\naudit_log:\n- action: created\n by: warrenlauren\n timestamp: '1982-02-19T17:59:18.620684'\n- action: created\n by: robertblackburn\n timestamp: '1976-03-29T15:21:16.808589'\n- action: created\n by: csuarez\n timestamp: '2013-08-27T14:23:21.257692'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "sales_analytics",
"type": "conversion",
"prompt": "Convert the following XML to YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<sales_analytics>\n<period>Q1</period>\n<sales>1293</sales>\n<region>East Luke</region>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.493282</generated_at>\n<version>v3.0</version>\n<tags>always</tags>\n<tags>someone</tags>\n<tags>guy</tags>\n<tags>financial</tags>\n<tags>thought</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>warrenlauren</by>\n<timestamp>1982-02-19T17:59:18.620684</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>robertblackburn</by>\n<timestamp>1976-03-29T15:21:16.808589</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>csuarez</by>\n<timestamp>2013-08-27T14:23:21.257692</timestamp>\n</audit_log>\n</sales_analytics>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (period, sales, region...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nperiod: Q1\nsales: 1293\nregion: East Luke\nmeta_info:\n generated_at: '2026-01-22T04:03:06.493282'\n version: v3.0\n tags:\n - always\n - someone\n - guy\n - financial\n - thought\naudit_log:\n- action: created\n by: warrenlauren\n timestamp: '1982-02-19T17:59:18.620684'\n- action: created\n by: robertblackburn\n timestamp: '1976-03-29T15:21:16.808589'\n- action: created\n by: csuarez\n timestamp: '2013-08-27T14:23:21.257692'\n",
"estimated_tokens": 250
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Output structured data for error_log using JSON."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"timestamp\": \"2026-01-22T04:03:06.273770\",\n \"level\": \"ERROR\",\n \"message\": \"Degree we simply far technology.\"\n}"
}
] |
{
"format": "json",
"complexity": "simple",
"schema": "error_log",
"type": "generation",
"prompt": "Output structured data for error_log using JSON.",
"output": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"timestamp\": \"2026-01-22T04:03:06.273770\",\n \"level\": \"ERROR\",\n \"message\": \"Degree we simply far technology.\"\n}",
"estimated_tokens": 165
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Reformat the JSON below into TOML:\n{\n \"paper_id\": \"arXiv:2020.55123\",\n \"title\": \"Digitized holistic data-warehouse\",\n \"authors\": [\n {\n \"name\": \"Charles Bartlett\",\n \"affiliation\": \"Patel Ltd\",\n \"email\": \"ngay@example.com\"\n },\n {\n \"name\": \"Colleen Cross\",\n \"affiliation\": \"Collins Group\",\n \"email\": \"diazkenneth@example.org\"\n },\n {\n \"name\": \"Patricia Campbell\",\n \"affiliation\": \"Smith and Sons\",\n \"email\": \"grogers@example.org\"\n }\n ],\n \"abstract\": \"Customer claim still follow together age.\\nEffort another tell ever sort child thing. Every yet call former image best throughout. Share call international name national.\",\n \"keywords\": [\n \"different\",\n \"prove\",\n \"her\",\n \"day\",\n \"likely\",\n \"two\"\n ],\n \"publication\": {\n \"venue\": \"ICLR\",\n \"year\": 2020,\n \"doi\": \"10.4579/vDOg\"\n },\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.158403\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"name\",\n \"finish\",\n \"skin\",\n \"recent\",\n \"store\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"lewistodd\",\n \"timestamp\": \"1985-10-15T20:04:05.021377\"\n }\n ]\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 8 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\npaper_id = \"arXiv:2020.55123\"\ntitle = \"Digitized holistic data-warehouse\"\nabstract = \"Customer claim still follow together age.\\nEffort another tell ever sort child thing. Every yet call former image best throughout. Share call international name national.\"\nkeywords = [ \"different\", \"prove\", \"her\", \"day\", \"likely\", \"two\",]\n[[authors]]\nname = \"Charles Bartlett\"\naffiliation = \"Patel Ltd\"\nemail = \"ngay@example.com\"\n\n[[authors]]\nname = \"Colleen Cross\"\naffiliation = \"Collins Group\"\nemail = \"diazkenneth@example.org\"\n\n[[authors]]\nname = \"Patricia Campbell\"\naffiliation = \"Smith and Sons\"\nemail = \"grogers@example.org\"\n\n[[audit_log]]\naction = \"created\"\nby = \"lewistodd\"\ntimestamp = \"1985-10-15T20:04:05.021377\"\n\n[publication]\nvenue = \"ICLR\"\nyear = 2020\ndoi = \"10.4579/vDOg\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:06.158403\"\nversion = \"v3.0\"\ntags = [ \"name\", \"finish\", \"skin\", \"recent\", \"store\",]\n"
}
] |
{
"format": "toml",
"complexity": "complex",
"schema": "research_paper",
"type": "conversion",
"prompt": "Reformat the JSON below into TOML:\n{\n \"paper_id\": \"arXiv:2020.55123\",\n \"title\": \"Digitized holistic data-warehouse\",\n \"authors\": [\n {\n \"name\": \"Charles Bartlett\",\n \"affiliation\": \"Patel Ltd\",\n \"email\": \"ngay@example.com\"\n },\n {\n \"name\": \"Colleen Cross\",\n \"affiliation\": \"Collins Group\",\n \"email\": \"diazkenneth@example.org\"\n },\n {\n \"name\": \"Patricia Campbell\",\n \"affiliation\": \"Smith and Sons\",\n \"email\": \"grogers@example.org\"\n }\n ],\n \"abstract\": \"Customer claim still follow together age.\\nEffort another tell ever sort child thing. Every yet call former image best throughout. Share call international name national.\",\n \"keywords\": [\n \"different\",\n \"prove\",\n \"her\",\n \"day\",\n \"likely\",\n \"two\"\n ],\n \"publication\": {\n \"venue\": \"ICLR\",\n \"year\": 2020,\n \"doi\": \"10.4579/vDOg\"\n },\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.158403\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"name\",\n \"finish\",\n \"skin\",\n \"recent\",\n \"store\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"lewistodd\",\n \"timestamp\": \"1985-10-15T20:04:05.021377\"\n }\n ]\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 8 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\npaper_id = \"arXiv:2020.55123\"\ntitle = \"Digitized holistic data-warehouse\"\nabstract = \"Customer claim still follow together age.\\nEffort another tell ever sort child thing. Every yet call former image best throughout. Share call international name national.\"\nkeywords = [ \"different\", \"prove\", \"her\", \"day\", \"likely\", \"two\",]\n[[authors]]\nname = \"Charles Bartlett\"\naffiliation = \"Patel Ltd\"\nemail = \"ngay@example.com\"\n\n[[authors]]\nname = \"Colleen Cross\"\naffiliation = \"Collins Group\"\nemail = \"diazkenneth@example.org\"\n\n[[authors]]\nname = \"Patricia Campbell\"\naffiliation = \"Smith and Sons\"\nemail = \"grogers@example.org\"\n\n[[audit_log]]\naction = \"created\"\nby = \"lewistodd\"\ntimestamp = \"1985-10-15T20:04:05.021377\"\n\n[publication]\nvenue = \"ICLR\"\nyear = 2020\ndoi = \"10.4579/vDOg\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:06.158403\"\nversion = \"v3.0\"\ntags = [ \"name\", \"finish\", \"skin\", \"recent\", \"store\",]\n",
"estimated_tokens": 367
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Transform this data from JSON to CSV:\n{\n \"contract\": \"syndicate open-source e-commerce\",\n \"parties\": [\n \"Lawrence PLC\",\n \"Glover-Miller\"\n ],\n \"signed\": true,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:05.172344\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"one\",\n \"year\",\n \"family\",\n \"boy\",\n \"ability\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"michelefloyd\",\n \"timestamp\": \"2012-10-17T22:03:38.225306\"\n },\n {\n \"action\": \"created\",\n \"by\": \"haleyrebecca\",\n \"timestamp\": \"1975-12-22T08:49:25.622175\"\n },\n {\n \"action\": \"created\",\n \"by\": \"juliamckee\",\n \"timestamp\": \"2018-10-12T06:08:50.601897\"\n }\n ]\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (contract, parties, signed...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncontract,parties,signed,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nsyndicate open-source e-commerce,\"[\"\"Lawrence PLC\"\", \"\"Glover-Miller\"\"]\",True,2026-01-22T04:03:05.172344,v3.0,\"[\"\"one\"\", \"\"year\"\", \"\"family\"\", \"\"boy\"\", \"\"ability\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"michelefloyd\"\", \"\"timestamp\"\": \"\"2012-10-17T22:03:38.225306\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"haleyrebecca\"\", \"\"timestamp\"\": \"\"1975-12-22T08:49:25.622175\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"juliamckee\"\", \"\"timestamp\"\": \"\"2018-10-12T06:08:50.601897\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "contract",
"type": "conversion",
"prompt": "Transform this data from JSON to CSV:\n{\n \"contract\": \"syndicate open-source e-commerce\",\n \"parties\": [\n \"Lawrence PLC\",\n \"Glover-Miller\"\n ],\n \"signed\": true,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:05.172344\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"one\",\n \"year\",\n \"family\",\n \"boy\",\n \"ability\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"michelefloyd\",\n \"timestamp\": \"2012-10-17T22:03:38.225306\"\n },\n {\n \"action\": \"created\",\n \"by\": \"haleyrebecca\",\n \"timestamp\": \"1975-12-22T08:49:25.622175\"\n },\n {\n \"action\": \"created\",\n \"by\": \"juliamckee\",\n \"timestamp\": \"2018-10-12T06:08:50.601897\"\n }\n ]\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (contract, parties, signed...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncontract,parties,signed,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nsyndicate open-source e-commerce,\"[\"\"Lawrence PLC\"\", \"\"Glover-Miller\"\"]\",True,2026-01-22T04:03:05.172344,v3.0,\"[\"\"one\"\", \"\"year\"\", \"\"family\"\", \"\"boy\"\", \"\"ability\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"michelefloyd\"\", \"\"timestamp\"\": \"\"2012-10-17T22:03:38.225306\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"haleyrebecca\"\", \"\"timestamp\"\": \"\"1975-12-22T08:49:25.622175\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"juliamckee\"\", \"\"timestamp\"\": \"\"2018-10-12T06:08:50.601897\"\"}]\"\r\n",
"estimated_tokens": 288
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Convert the following XML to YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>moyerjohn</user>\n<post>Team writer should. Democratic tree in doctor leg enter feeling stay.</post>\n<likes>135</likes>\n</social_media_post>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser: moyerjohn\npost: Team writer should. Democratic tree in doctor leg enter feeling stay.\nlikes: 135\n"
}
] |
{
"format": "yaml",
"complexity": "simple",
"schema": "social_media_post",
"type": "conversion",
"prompt": "Convert the following XML to YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>moyerjohn</user>\n<post>Team writer should. Democratic tree in doctor leg enter feeling stay.</post>\n<likes>135</likes>\n</social_media_post>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser: moyerjohn\npost: Team writer should. Democratic tree in doctor leg enter feeling stay.\nlikes: 135\n",
"estimated_tokens": 168
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Output structured data for transaction_record using YAML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ntxn: 65129b6d-3a7e-4539-b313-cfd54baa3601\namount: 146.7\nstatus: completed\nmeta_info:\n generated_at: '2026-01-22T04:03:06.215611'\n version: v1.0\n tags:\n - because\n - everyone\n - particularly\n - reveal\n - education\naudit_log:\n- action: created\n by: ocline\n timestamp: '2006-09-27T15:52:18.113473'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "transaction_record",
"type": "generation",
"prompt": "Output structured data for transaction_record using YAML.",
"output": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ntxn: 65129b6d-3a7e-4539-b313-cfd54baa3601\namount: 146.7\nstatus: completed\nmeta_info:\n generated_at: '2026-01-22T04:03:06.215611'\n version: v1.0\n tags:\n - because\n - everyone\n - particularly\n - reveal\n - education\naudit_log:\n- action: created\n by: ocline\n timestamp: '2006-09-27T15:52:18.113473'\n",
"estimated_tokens": 214
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following TOML to XML:\nid = \"1d9061f2-fb53-4be8-acad-6da5016ea71d\"\npatient = \"Jon Hawkins\"\ndiagnosis = \"fear\"\nnotes = \"Once sell station between office wall popular. When there shoulder.\\nLive these personal activity. Road teach concern. Song theory story total note suddenly already international.\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 4 root fields (id, patient, diagnosis...) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<clinical_note>\n<id>1d9061f2-fb53-4be8-acad-6da5016ea71d</id>\n<patient>Jon Hawkins</patient>\n<diagnosis>fear</diagnosis>\n<notes>Once sell station between office wall popular. When there shoulder.\nLive these personal activity. Road teach concern. Song theory story total note suddenly already international.</notes>\n</clinical_note>"
}
] |
{
"format": "xml",
"complexity": "simple",
"schema": "clinical_note",
"type": "conversion",
"prompt": "Convert the following TOML to XML:\nid = \"1d9061f2-fb53-4be8-acad-6da5016ea71d\"\npatient = \"Jon Hawkins\"\ndiagnosis = \"fear\"\nnotes = \"Once sell station between office wall popular. When there shoulder.\\nLive these personal activity. Road teach concern. Song theory story total note suddenly already international.\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 4 root fields (id, patient, diagnosis...) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<clinical_note>\n<id>1d9061f2-fb53-4be8-acad-6da5016ea71d</id>\n<patient>Jon Hawkins</patient>\n<diagnosis>fear</diagnosis>\n<notes>Once sell station between office wall popular. When there shoulder.\nLive these personal activity. Road teach concern. Song theory story total note suddenly already international.</notes>\n</clinical_note>",
"estimated_tokens": 237
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Output structured data for course_syllabus using JSON."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"course\": \"Adaptive value-added knowledge user\",\n \"weeks\": 10,\n \"credits\": 3\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "course_syllabus",
"type": "generation",
"prompt": "Output structured data for course_syllabus using JSON.",
"output": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"course\": \"Adaptive value-added knowledge user\",\n \"weeks\": 10,\n \"credits\": 3\n}",
"estimated_tokens": 158
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Reformat the TOML below into XML:\nstudent = \"Kelly Tucker\"\nscore = 82\ngrade = \"B\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>Kelly Tucker</student>\n<score>82</score>\n<grade>B</grade>\n</student_assessment>"
}
] |
{
"format": "xml",
"complexity": "simple",
"schema": "student_assessment",
"type": "conversion",
"prompt": "Reformat the TOML below into XML:\nstudent = \"Kelly Tucker\"\nscore = 82\ngrade = \"B\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>Kelly Tucker</student>\n<score>82</score>\n<grade>B</grade>\n</student_assessment>",
"estimated_tokens": 181
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Generate error log data in XML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:06.821685</timestamp>\n<level>ERROR</level>\n<message>Follow perform image fight end drop.</message>\n</error_log>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "error_log",
"type": "generation",
"prompt": "Generate error log data in XML format.",
"output": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:06.821685</timestamp>\n<level>ERROR</level>\n<message>Follow perform image fight end drop.</message>\n</error_log>",
"estimated_tokens": 185
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following CSV to XML:\nuser,rating,comment,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\njeffersonjames,4,Medical myself however weight admit for likely say.,2026-01-22T04:03:05.096294,v1.0,\"[\"\"note\"\", \"\"police\"\", \"\"offer\"\", \"\"sing\"\", \"\"friend\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"jenniferbartlett\"\", \"\"timestamp\"\": \"\"2023-09-11T15:31:12.547088\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"ahoward\"\", \"\"timestamp\"\": \"\"1992-07-11T20:06:55.844429\"\"}]\"\r\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>jeffersonjames</user>\n<rating>4</rating>\n<comment>Medical myself however weight admit for likely say.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.096294</generated_at>\n<version>v1.0</version>\n<tags>note</tags>\n<tags>police</tags>\n<tags>offer</tags>\n<tags>sing</tags>\n<tags>friend</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>jenniferbartlett</by>\n<timestamp>2023-09-11T15:31:12.547088</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>ahoward</by>\n<timestamp>1992-07-11T20:06:55.844429</timestamp>\n</audit_log>\n</customer_review>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "customer_review",
"type": "conversion",
"prompt": "Convert the following CSV to XML:\nuser,rating,comment,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\njeffersonjames,4,Medical myself however weight admit for likely say.,2026-01-22T04:03:05.096294,v1.0,\"[\"\"note\"\", \"\"police\"\", \"\"offer\"\", \"\"sing\"\", \"\"friend\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"jenniferbartlett\"\", \"\"timestamp\"\": \"\"2023-09-11T15:31:12.547088\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"ahoward\"\", \"\"timestamp\"\": \"\"1992-07-11T20:06:55.844429\"\"}]\"\r\n",
"output": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>jeffersonjames</user>\n<rating>4</rating>\n<comment>Medical myself however weight admit for likely say.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.096294</generated_at>\n<version>v1.0</version>\n<tags>note</tags>\n<tags>police</tags>\n<tags>offer</tags>\n<tags>sing</tags>\n<tags>friend</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>jenniferbartlett</by>\n<timestamp>2023-09-11T15:31:12.547088</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>ahoward</by>\n<timestamp>1992-07-11T20:06:55.844429</timestamp>\n</audit_log>\n</customer_review>",
"estimated_tokens": 303
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Generate product listing data in TOML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct = \"poor\"\nprice = 73.89\nstock = 4\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "product_listing",
"type": "generation",
"prompt": "Generate product listing data in TOML format.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct = \"poor\"\nprice = 73.89\nstock = 4\n",
"estimated_tokens": 145
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Output structured data for lab_result using CSV."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nid,test,value\r\n897a27ea-8fb5-420c-b42b-e1a5c40c2759,later,99.72910826248814\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "lab_result",
"type": "generation",
"prompt": "Output structured data for lab_result using CSV.",
"output": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nid,test,value\r\n897a27ea-8fb5-420c-b42b-e1a5c40c2759,later,99.72910826248814\r\n",
"estimated_tokens": 157
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Output structured data for clinical_note using JSON."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The clinical_note should contain a dictionary with 6 root fields (id, patient, diagnosis...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"id\": \"faf6572c-1f63-4642-90a4-4fc20e61e457\",\n \"patient\": \"Amanda Bell\",\n \"diagnosis\": \"smile\",\n \"notes\": \"Action alone science season ago. Law better eight them everyone theory affect. Capital law situation practice trouble.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.298547\",\n \"version\": \"v4.0\",\n \"tags\": [\n \"understand\",\n \"feel\",\n \"floor\",\n \"me\",\n \"especially\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"tiffanyberg\",\n \"timestamp\": \"2002-12-14T15:01:11.646925\"\n },\n {\n \"action\": \"created\",\n \"by\": \"michaelsmith\",\n \"timestamp\": \"2013-08-03T12:02:23.573499\"\n },\n {\n \"action\": \"created\",\n \"by\": \"melissa10\",\n \"timestamp\": \"1980-07-10T18:06:08.132136\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "clinical_note",
"type": "generation",
"prompt": "Output structured data for clinical_note using JSON.",
"output": "Approach:\n1. Define the schema: The clinical_note should contain a dictionary with 6 root fields (id, patient, diagnosis...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"id\": \"faf6572c-1f63-4642-90a4-4fc20e61e457\",\n \"patient\": \"Amanda Bell\",\n \"diagnosis\": \"smile\",\n \"notes\": \"Action alone science season ago. Law better eight them everyone theory affect. Capital law situation practice trouble.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.298547\",\n \"version\": \"v4.0\",\n \"tags\": [\n \"understand\",\n \"feel\",\n \"floor\",\n \"me\",\n \"especially\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"tiffanyberg\",\n \"timestamp\": \"2002-12-14T15:01:11.646925\"\n },\n {\n \"action\": \"created\",\n \"by\": \"michaelsmith\",\n \"timestamp\": \"2013-08-03T12:02:23.573499\"\n },\n {\n \"action\": \"created\",\n \"by\": \"melissa10\",\n \"timestamp\": \"1980-07-10T18:06:08.132136\"\n }\n ]\n}",
"estimated_tokens": 336
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Reformat the CSV below into JSON:\nstudent,score,grade\r\nRobert Lopez,6,B\r\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"student\": \"Robert Lopez\",\n \"score\": 6,\n \"grade\": \"B\"\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "student_assessment",
"type": "conversion",
"prompt": "Reformat the CSV below into JSON:\nstudent,score,grade\r\nRobert Lopez,6,B\r\n",
"output": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"student\": \"Robert Lopez\",\n \"score\": 6,\n \"grade\": \"B\"\n}",
"estimated_tokens": 158
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Create a XML representation of student assessment."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The student_assessment should contain a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>John Phillips</student>\n<score>18</score>\n<grade>A</grade>\n</student_assessment>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "student_assessment",
"type": "generation",
"prompt": "Create a XML representation of student assessment.",
"output": "Approach:\n1. Define the schema: The student_assessment should contain a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>John Phillips</student>\n<score>18</score>\n<grade>A</grade>\n</student_assessment>",
"estimated_tokens": 176
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Generate api specification data in CSV format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 5 root fields (endpoint, method, responses...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nendpoint,method,responses.200,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\n/api/v1/users,GET,OK,2026-01-22T04:03:05.057559,v3.0,\"[\"\"respond\"\", \"\"week\"\", \"\"across\"\", \"\"market\"\", \"\"they\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"lmclaughlin\"\", \"\"timestamp\"\": \"\"2005-02-11T13:11:29.129834\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"verickson\"\", \"\"timestamp\"\": \"\"2002-03-12T22:49:54.265695\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"hwilliams\"\", \"\"timestamp\"\": \"\"1980-12-27T10:13:52.544021\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "api_specification",
"type": "generation",
"prompt": "Generate api specification data in CSV format.",
"output": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 5 root fields (endpoint, method, responses...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nendpoint,method,responses.200,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\n/api/v1/users,GET,OK,2026-01-22T04:03:05.057559,v3.0,\"[\"\"respond\"\", \"\"week\"\", \"\"across\"\", \"\"market\"\", \"\"they\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"lmclaughlin\"\", \"\"timestamp\"\": \"\"2005-02-11T13:11:29.129834\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"verickson\"\", \"\"timestamp\"\": \"\"2002-03-12T22:49:54.265695\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"hwilliams\"\", \"\"timestamp\"\": \"\"1980-12-27T10:13:52.544021\"\"}]\"\r\n",
"estimated_tokens": 270
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Reformat the XML below into JSON:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>staceysalazar</user>\n<post>Remember say produce hit decade include thought. Sit green force table prove. Political season administration.</post>\n<likes>154</likes>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.716958</generated_at>\n<version>v3.0</version>\n<tags>child</tags>\n<tags>red</tags>\n<tags>small</tags>\n<tags>late</tags>\n<tags>sometimes</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>michael81</by>\n<timestamp>2005-02-24T19:33:58.673431</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>lisa65</by>\n<timestamp>1992-08-02T16:56:20.836960</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>sethshields</by>\n<timestamp>2024-07-21T13:32:39.224149</timestamp>\n</audit_log>\n</social_media_post>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"user\": \"staceysalazar\",\n \"post\": \"Remember say produce hit decade include thought. Sit green force table prove. Political season administration.\",\n \"likes\": 154,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.716958\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"child\",\n \"red\",\n \"small\",\n \"late\",\n \"sometimes\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"michael81\",\n \"timestamp\": \"2005-02-24T19:33:58.673431\"\n },\n {\n \"action\": \"created\",\n \"by\": \"lisa65\",\n \"timestamp\": \"1992-08-02T16:56:20.836960\"\n },\n {\n \"action\": \"created\",\n \"by\": \"sethshields\",\n \"timestamp\": \"2024-07-21T13:32:39.224149\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "social_media_post",
"type": "conversion",
"prompt": "Reformat the XML below into JSON:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>staceysalazar</user>\n<post>Remember say produce hit decade include thought. Sit green force table prove. Political season administration.</post>\n<likes>154</likes>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.716958</generated_at>\n<version>v3.0</version>\n<tags>child</tags>\n<tags>red</tags>\n<tags>small</tags>\n<tags>late</tags>\n<tags>sometimes</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>michael81</by>\n<timestamp>2005-02-24T19:33:58.673431</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>lisa65</by>\n<timestamp>1992-08-02T16:56:20.836960</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>sethshields</by>\n<timestamp>2024-07-21T13:32:39.224149</timestamp>\n</audit_log>\n</social_media_post>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"user\": \"staceysalazar\",\n \"post\": \"Remember say produce hit decade include thought. Sit green force table prove. Political season administration.\",\n \"likes\": 154,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.716958\",\n \"version\": \"v3.0\",\n \"tags\": [\n \"child\",\n \"red\",\n \"small\",\n \"late\",\n \"sometimes\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"michael81\",\n \"timestamp\": \"2005-02-24T19:33:58.673431\"\n },\n {\n \"action\": \"created\",\n \"by\": \"lisa65\",\n \"timestamp\": \"1992-08-02T16:56:20.836960\"\n },\n {\n \"action\": \"created\",\n \"by\": \"sethshields\",\n \"timestamp\": \"2024-07-21T13:32:39.224149\"\n }\n ]\n}",
"estimated_tokens": 322
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Generate transaction record data in TOML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ntxn = \"b5419c9f-44d8-4ece-83e3-af9c3d23a56f\"\namount = 7.37\nstatus = \"completed\"\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "transaction_record",
"type": "generation",
"prompt": "Generate transaction record data in TOML format.",
"output": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ntxn = \"b5419c9f-44d8-4ece-83e3-af9c3d23a56f\"\namount = 7.37\nstatus = \"completed\"\n",
"estimated_tokens": 155
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Output structured data for experiment_result using XML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The experiment_result should contain a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<experiment_result>\n<experiment_id>EXP-712069</experiment_id>\n<title>Analysis of hard</title>\n<metrics>\n<accuracy>0.902</accuracy>\n<loss>0.1319</loss>\n<epoch>85</epoch>\n</metrics>\n<config>\n<batch_size>64</batch_size>\n<optimizer>adam</optimizer>\n<lr>0.001</lr>\n</config>\n</experiment_result>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "experiment_result",
"type": "generation",
"prompt": "Output structured data for experiment_result using XML.",
"output": "Approach:\n1. Define the schema: The experiment_result should contain a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<experiment_result>\n<experiment_id>EXP-712069</experiment_id>\n<title>Analysis of hard</title>\n<metrics>\n<accuracy>0.902</accuracy>\n<loss>0.1319</loss>\n<epoch>85</epoch>\n</metrics>\n<config>\n<batch_size>64</batch_size>\n<optimizer>adam</optimizer>\n<lr>0.001</lr>\n</config>\n</experiment_result>",
"estimated_tokens": 223
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Output structured data for sales_analytics using XML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The sales_analytics should contain a dictionary with 3 root fields (period, sales, region) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<sales_analytics>\n<period>Q1</period>\n<sales>3806</sales>\n<region>West Anitaville</region>\n</sales_analytics>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "sales_analytics",
"type": "generation",
"prompt": "Output structured data for sales_analytics using XML.",
"output": "Approach:\n1. Define the schema: The sales_analytics should contain a dictionary with 3 root fields (period, sales, region) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<sales_analytics>\n<period>Q1</period>\n<sales>3806</sales>\n<region>West Anitaville</region>\n</sales_analytics>",
"estimated_tokens": 175
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following TOML to XML:\ncourse = \"Secured national structure\"\nweeks = 9\ncredits = 3\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<course_syllabus>\n<course>Secured national structure</course>\n<weeks>9</weeks>\n<credits>3</credits>\n</course_syllabus>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "course_syllabus",
"type": "conversion",
"prompt": "Convert the following TOML to XML:\ncourse = \"Secured national structure\"\nweeks = 9\ncredits = 3\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<course_syllabus>\n<course>Secured national structure</course>\n<weeks>9</weeks>\n<credits>3</credits>\n</course_syllabus>",
"estimated_tokens": 183
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Generate lab result data in JSON format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"id\": \"6e591c2c-cc68-4d05-ac15-c20ef70f7229\",\n \"test\": \"board\",\n \"value\": 55.329482418139975\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "lab_result",
"type": "generation",
"prompt": "Generate lab result data in JSON format.",
"output": "Approach:\n1. Define the schema: The lab_result should contain a dictionary with 3 root fields (id, test, value) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"id\": \"6e591c2c-cc68-4d05-ac15-c20ef70f7229\",\n \"test\": \"board\",\n \"value\": 55.329482418139975\n}",
"estimated_tokens": 159
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Generate product listing data in JSON format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 5 root fields (product, price, stock...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"product\": \"there\",\n \"price\": 46.25,\n \"stock\": 34,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:04.998742\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"camera\",\n \"news\",\n \"kid\",\n \"for\",\n \"own\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"bakerstacy\",\n \"timestamp\": \"2000-11-04T10:52:59.673937\"\n },\n {\n \"action\": \"created\",\n \"by\": \"gsmith\",\n \"timestamp\": \"2021-07-21T12:03:17.086905\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "product_listing",
"type": "generation",
"prompt": "Generate product listing data in JSON format.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 5 root fields (product, price, stock...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"product\": \"there\",\n \"price\": 46.25,\n \"stock\": 34,\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:04.998742\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"camera\",\n \"news\",\n \"kid\",\n \"for\",\n \"own\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"bakerstacy\",\n \"timestamp\": \"2000-11-04T10:52:59.673937\"\n },\n {\n \"action\": \"created\",\n \"by\": \"gsmith\",\n \"timestamp\": \"2021-07-21T12:03:17.086905\"\n }\n ]\n}",
"estimated_tokens": 259
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Generate product listing data in CSV format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 5 root fields (product, price, stock...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct,price,stock,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nguess,38.69,37,2026-01-22T04:03:07.009581,v3.0,\"[\"\"though\"\", \"\"fall\"\", \"\"she\"\", \"\"pass\"\", \"\"though\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"millercameron\"\", \"\"timestamp\"\": \"\"1987-09-07T04:14:05.471635\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"bryantsabrina\"\", \"\"timestamp\"\": \"\"1976-08-01T23:58:31.998373\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"gpatterson\"\", \"\"timestamp\"\": \"\"1997-07-15T19:10:47.077986\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "product_listing",
"type": "generation",
"prompt": "Generate product listing data in CSV format.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 5 root fields (product, price, stock...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct,price,stock,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nguess,38.69,37,2026-01-22T04:03:07.009581,v3.0,\"[\"\"though\"\", \"\"fall\"\", \"\"she\"\", \"\"pass\"\", \"\"though\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"millercameron\"\", \"\"timestamp\"\": \"\"1987-09-07T04:14:05.471635\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"bryantsabrina\"\", \"\"timestamp\"\": \"\"1976-08-01T23:58:31.998373\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"gpatterson\"\", \"\"timestamp\"\": \"\"1997-07-15T19:10:47.077986\"\"}]\"\r\n",
"estimated_tokens": 265
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Create a CSV representation of financial report."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The financial_report should contain a dictionary with 5 root fields (company, revenue, profit...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncompany,revenue,profit,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nSkinner Ltd,830953,93279,2026-01-22T04:03:05.100685,v2.0,\"[\"\"artist\"\", \"\"know\"\", \"\"appear\"\", \"\"well\"\", \"\"role\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"valerie40\"\", \"\"timestamp\"\": \"\"2014-09-29T07:24:14.273386\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"brandy04\"\", \"\"timestamp\"\": \"\"1988-04-13T17:50:16.124494\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "financial_report",
"type": "generation",
"prompt": "Create a CSV representation of financial report.",
"output": "Approach:\n1. Define the schema: The financial_report should contain a dictionary with 5 root fields (company, revenue, profit...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncompany,revenue,profit,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nSkinner Ltd,830953,93279,2026-01-22T04:03:05.100685,v2.0,\"[\"\"artist\"\", \"\"know\"\", \"\"appear\"\", \"\"well\"\", \"\"role\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"valerie40\"\", \"\"timestamp\"\": \"\"2014-09-29T07:24:14.273386\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"brandy04\"\", \"\"timestamp\"\": \"\"1988-04-13T17:50:16.124494\"\"}]\"\r\n",
"estimated_tokens": 243
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Transform this data from CSV to TOML:\ncontract,parties,signed\r\ndeliver web-enabled vortals,\"[\"\"Murphy Inc\"\", \"\"Neal-Wolf\"\"]\",True\r\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncontract = \"deliver web-enabled vortals\"\nparties = [ \"Murphy Inc\", \"Neal-Wolf\",]\nsigned = true\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "contract",
"type": "conversion",
"prompt": "Transform this data from CSV to TOML:\ncontract,parties,signed\r\ndeliver web-enabled vortals,\"[\"\"Murphy Inc\"\", \"\"Neal-Wolf\"\"]\",True\r\n",
"output": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncontract = \"deliver web-enabled vortals\"\nparties = [ \"Murphy Inc\", \"Neal-Wolf\",]\nsigned = true\n",
"estimated_tokens": 165
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Generate product listing data in CSV format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 5 root fields (product, price, stock...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct,price,stock,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nreason,97.18,46,2026-01-22T04:03:06.613948,v5.0,\"[\"\"grow\"\", \"\"include\"\", \"\"close\"\", \"\"decision\"\", \"\"loss\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"paulbowman\"\", \"\"timestamp\"\": \"\"1987-02-25T23:48:21.906535\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"michaela33\"\", \"\"timestamp\"\": \"\"1972-03-21T00:44:22.319687\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"pavery\"\", \"\"timestamp\"\": \"\"1972-02-24T04:42:29.868387\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "product_listing",
"type": "generation",
"prompt": "Generate product listing data in CSV format.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 5 root fields (product, price, stock...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct,price,stock,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nreason,97.18,46,2026-01-22T04:03:06.613948,v5.0,\"[\"\"grow\"\", \"\"include\"\", \"\"close\"\", \"\"decision\"\", \"\"loss\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"paulbowman\"\", \"\"timestamp\"\": \"\"1987-02-25T23:48:21.906535\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"michaela33\"\", \"\"timestamp\"\": \"\"1972-03-21T00:44:22.319687\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"pavery\"\", \"\"timestamp\"\": \"\"1972-02-24T04:42:29.868387\"\"}]\"\r\n",
"estimated_tokens": 264
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Convert the following XML to JSON:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>kpowers</user>\n<post>Article stage how final development receive front. Perhaps forward scientist need. Agree such civil loss agent those child very.</post>\n<likes>909</likes>\n</social_media_post>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"user\": \"kpowers\",\n \"post\": \"Article stage how final development receive front. Perhaps forward scientist need. Agree such civil loss agent those child very.\",\n \"likes\": 909\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "social_media_post",
"type": "conversion",
"prompt": "Convert the following XML to JSON:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>kpowers</user>\n<post>Article stage how final development receive front. Perhaps forward scientist need. Agree such civil loss agent those child very.</post>\n<likes>909</likes>\n</social_media_post>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"user\": \"kpowers\",\n \"post\": \"Article stage how final development receive front. Perhaps forward scientist need. Agree such civil loss agent those child very.\",\n \"likes\": 909\n}",
"estimated_tokens": 187
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Create a YAML representation of api specification."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nendpoint: /api/v1/users\nmethod: GET\nresponses:\n '200': OK\n"
}
] |
{
"format": "yaml",
"complexity": "simple",
"schema": "api_specification",
"type": "generation",
"prompt": "Create a YAML representation of api specification.",
"output": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nendpoint: /api/v1/users\nmethod: GET\nresponses:\n '200': OK\n",
"estimated_tokens": 154
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Generate transaction record data in JSON format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"txn\": \"a2a21367-3995-4fc1-9134-9127b3dce120\",\n \"amount\": 370.83,\n \"status\": \"completed\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.201416\",\n \"version\": \"v4.0\",\n \"tags\": [\n \"major\",\n \"about\",\n \"yourself\",\n \"would\",\n \"maintain\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"ernestjacobs\",\n \"timestamp\": \"1974-08-10T15:07:17.873548\"\n },\n {\n \"action\": \"created\",\n \"by\": \"bharmon\",\n \"timestamp\": \"1983-06-17T10:13:31.692769\"\n },\n {\n \"action\": \"created\",\n \"by\": \"madisonwashington\",\n \"timestamp\": \"1985-08-19T18:37:31.167179\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "transaction_record",
"type": "generation",
"prompt": "Generate transaction record data in JSON format.",
"output": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"txn\": \"a2a21367-3995-4fc1-9134-9127b3dce120\",\n \"amount\": 370.83,\n \"status\": \"completed\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.201416\",\n \"version\": \"v4.0\",\n \"tags\": [\n \"major\",\n \"about\",\n \"yourself\",\n \"would\",\n \"maintain\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"ernestjacobs\",\n \"timestamp\": \"1974-08-10T15:07:17.873548\"\n },\n {\n \"action\": \"created\",\n \"by\": \"bharmon\",\n \"timestamp\": \"1983-06-17T10:13:31.692769\"\n },\n {\n \"action\": \"created\",\n \"by\": \"madisonwashington\",\n \"timestamp\": \"1985-08-19T18:37:31.167179\"\n }\n ]\n}",
"estimated_tokens": 303
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Transform this data from TOML to YAML:\ntimestamp = \"2026-01-22T04:03:06.848557\"\nlevel = \"ERROR\"\nmessage = \"Condition talk down.\"\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntimestamp: '2026-01-22T04:03:06.848557'\nlevel: ERROR\nmessage: Condition talk down.\n"
}
] |
{
"format": "yaml",
"complexity": "medium",
"schema": "error_log",
"type": "conversion",
"prompt": "Transform this data from TOML to YAML:\ntimestamp = \"2026-01-22T04:03:06.848557\"\nlevel = \"ERROR\"\nmessage = \"Condition talk down.\"\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntimestamp: '2026-01-22T04:03:06.848557'\nlevel: ERROR\nmessage: Condition talk down.\n",
"estimated_tokens": 165
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Transform this data from TOML to YAML:\ntxn = \"a2a21367-3995-4fc1-9134-9127b3dce120\"\namount = 370.83\nstatus = \"completed\"\n[[audit_log]]\naction = \"created\"\nby = \"ernestjacobs\"\ntimestamp = \"1974-08-10T15:07:17.873548\"\n\n[[audit_log]]\naction = \"created\"\nby = \"bharmon\"\ntimestamp = \"1983-06-17T10:13:31.692769\"\n\n[[audit_log]]\naction = \"created\"\nby = \"madisonwashington\"\ntimestamp = \"1985-08-19T18:37:31.167179\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.201416\"\nversion = \"v4.0\"\ntags = [ \"major\", \"about\", \"yourself\", \"would\", \"maintain\",]\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntxn: a2a21367-3995-4fc1-9134-9127b3dce120\namount: 370.83\nstatus: completed\nmeta_info:\n generated_at: '2026-01-22T04:03:07.201416'\n version: v4.0\n tags:\n - major\n - about\n - yourself\n - would\n - maintain\naudit_log:\n- action: created\n by: ernestjacobs\n timestamp: '1974-08-10T15:07:17.873548'\n- action: created\n by: bharmon\n timestamp: '1983-06-17T10:13:31.692769'\n- action: created\n by: madisonwashington\n timestamp: '1985-08-19T18:37:31.167179'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "transaction_record",
"type": "conversion",
"prompt": "Transform this data from TOML to YAML:\ntxn = \"a2a21367-3995-4fc1-9134-9127b3dce120\"\namount = 370.83\nstatus = \"completed\"\n[[audit_log]]\naction = \"created\"\nby = \"ernestjacobs\"\ntimestamp = \"1974-08-10T15:07:17.873548\"\n\n[[audit_log]]\naction = \"created\"\nby = \"bharmon\"\ntimestamp = \"1983-06-17T10:13:31.692769\"\n\n[[audit_log]]\naction = \"created\"\nby = \"madisonwashington\"\ntimestamp = \"1985-08-19T18:37:31.167179\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.201416\"\nversion = \"v4.0\"\ntags = [ \"major\", \"about\", \"yourself\", \"would\", \"maintain\",]\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ntxn: a2a21367-3995-4fc1-9134-9127b3dce120\namount: 370.83\nstatus: completed\nmeta_info:\n generated_at: '2026-01-22T04:03:07.201416'\n version: v4.0\n tags:\n - major\n - about\n - yourself\n - would\n - maintain\naudit_log:\n- action: created\n by: ernestjacobs\n timestamp: '1974-08-10T15:07:17.873548'\n- action: created\n by: bharmon\n timestamp: '1983-06-17T10:13:31.692769'\n- action: created\n by: madisonwashington\n timestamp: '1985-08-19T18:37:31.167179'\n",
"estimated_tokens": 258
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Convert the following YAML to CSV:\nendpoint: /api/v1/users\nmethod: GET\nresponses:\n '200': OK\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nendpoint,method,responses.200\r\n/api/v1/users,GET,OK\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "api_specification",
"type": "conversion",
"prompt": "Convert the following YAML to CSV:\nendpoint: /api/v1/users\nmethod: GET\nresponses:\n '200': OK\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nendpoint,method,responses.200\r\n/api/v1/users,GET,OK\r\n",
"estimated_tokens": 162
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Generate news article data in XML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<news_article>\n<headline>Consumer say specific.</headline>\n<body>Enjoy adult professional garden oil easy tax technology. Nearly across sure physical least everyone buy. Continue more realize star.</body>\n<author>Damon Cisneros</author>\n</news_article>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "news_article",
"type": "generation",
"prompt": "Generate news article data in XML format.",
"output": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<news_article>\n<headline>Consumer say specific.</headline>\n<body>Enjoy adult professional garden oil easy tax technology. Nearly across sure physical least everyone buy. Continue more realize star.</body>\n<author>Damon Cisneros</author>\n</news_article>",
"estimated_tokens": 210
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Output structured data for contract using YAML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncontract: synthesize world-class info-mediaries\nparties:\n- Greene, Hayes and Jones\n- Henson Group\nsigned: true\n"
}
] |
{
"format": "yaml",
"complexity": "medium",
"schema": "contract",
"type": "generation",
"prompt": "Output structured data for contract using YAML.",
"output": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncontract: synthesize world-class info-mediaries\nparties:\n- Greene, Hayes and Jones\n- Henson Group\nsigned: true\n",
"estimated_tokens": 164
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Convert the following YAML to JSON:\nperiod: Q1\nsales: 1573\nregion: Dunnview\nmeta_info:\n generated_at: '2026-01-22T04:03:07.297151'\n version: v5.0\n tags:\n - real\n - word\n - show\n - land\n - over\naudit_log:\n- action: created\n by: michael49\n timestamp: '2014-08-19T12:53:38.260481'\n- action: created\n by: david08\n timestamp: '1992-08-27T05:51:20.774593'\n- action: created\n by: john53\n timestamp: '2022-06-25T13:06:39.665068'\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 5 root fields (period, sales, region...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"period\": \"Q1\",\n \"sales\": 1573,\n \"region\": \"Dunnview\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.297151\",\n \"version\": \"v5.0\",\n \"tags\": [\n \"real\",\n \"word\",\n \"show\",\n \"land\",\n \"over\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"michael49\",\n \"timestamp\": \"2014-08-19T12:53:38.260481\"\n },\n {\n \"action\": \"created\",\n \"by\": \"david08\",\n \"timestamp\": \"1992-08-27T05:51:20.774593\"\n },\n {\n \"action\": \"created\",\n \"by\": \"john53\",\n \"timestamp\": \"2022-06-25T13:06:39.665068\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "sales_analytics",
"type": "conversion",
"prompt": "Convert the following YAML to JSON:\nperiod: Q1\nsales: 1573\nregion: Dunnview\nmeta_info:\n generated_at: '2026-01-22T04:03:07.297151'\n version: v5.0\n tags:\n - real\n - word\n - show\n - land\n - over\naudit_log:\n- action: created\n by: michael49\n timestamp: '2014-08-19T12:53:38.260481'\n- action: created\n by: david08\n timestamp: '1992-08-27T05:51:20.774593'\n- action: created\n by: john53\n timestamp: '2022-06-25T13:06:39.665068'\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 5 root fields (period, sales, region...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"period\": \"Q1\",\n \"sales\": 1573,\n \"region\": \"Dunnview\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:07.297151\",\n \"version\": \"v5.0\",\n \"tags\": [\n \"real\",\n \"word\",\n \"show\",\n \"land\",\n \"over\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"michael49\",\n \"timestamp\": \"2014-08-19T12:53:38.260481\"\n },\n {\n \"action\": \"created\",\n \"by\": \"david08\",\n \"timestamp\": \"1992-08-27T05:51:20.774593\"\n },\n {\n \"action\": \"created\",\n \"by\": \"john53\",\n \"timestamp\": \"2022-06-25T13:06:39.665068\"\n }\n ]\n}",
"estimated_tokens": 294
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Output structured data for financial_report using XML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The financial_report should contain a dictionary with 5 root fields (company, revenue, profit...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<financial_report>\n<company>Collier, Davis and Foster</company>\n<revenue>916171</revenue>\n<profit>71292</profit>\n<meta_info>\n<generated_at>2026-01-22T04:03:07.325400</generated_at>\n<version>v4.0</version>\n<tags>than</tags>\n<tags>stand</tags>\n<tags>describe</tags>\n<tags>bill</tags>\n<tags>listen</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>robinsonsusan</by>\n<timestamp>2018-12-19T11:56:49.503023</timestamp>\n</audit_log>\n</financial_report>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "financial_report",
"type": "generation",
"prompt": "Output structured data for financial_report using XML.",
"output": "Approach:\n1. Define the schema: The financial_report should contain a dictionary with 5 root fields (company, revenue, profit...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<financial_report>\n<company>Collier, Davis and Foster</company>\n<revenue>916171</revenue>\n<profit>71292</profit>\n<meta_info>\n<generated_at>2026-01-22T04:03:07.325400</generated_at>\n<version>v4.0</version>\n<tags>than</tags>\n<tags>stand</tags>\n<tags>describe</tags>\n<tags>bill</tags>\n<tags>listen</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>robinsonsusan</by>\n<timestamp>2018-12-19T11:56:49.503023</timestamp>\n</audit_log>\n</financial_report>",
"estimated_tokens": 264
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Create a TOML representation of customer review."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser = \"nichole49\"\nrating = 3\ncomment = \"Phone phone series machine page race traditional.\"\n[[audit_log]]\naction = \"created\"\nby = \"jessica07\"\ntimestamp = \"2017-07-05T03:45:59.622835\"\n\n[[audit_log]]\naction = \"created\"\nby = \"justinanderson\"\ntimestamp = \"2011-07-01T21:39:10.009112\"\n\n[[audit_log]]\naction = \"created\"\nby = \"jessica79\"\ntimestamp = \"1978-09-24T13:44:40.210898\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.539337\"\nversion = \"v4.0\"\ntags = [ \"wait\", \"large\", \"business\", \"number\", \"young\",]\n"
}
] |
{
"format": "toml",
"complexity": "complex",
"schema": "customer_review",
"type": "generation",
"prompt": "Create a TOML representation of customer review.",
"output": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser = \"nichole49\"\nrating = 3\ncomment = \"Phone phone series machine page race traditional.\"\n[[audit_log]]\naction = \"created\"\nby = \"jessica07\"\ntimestamp = \"2017-07-05T03:45:59.622835\"\n\n[[audit_log]]\naction = \"created\"\nby = \"justinanderson\"\ntimestamp = \"2011-07-01T21:39:10.009112\"\n\n[[audit_log]]\naction = \"created\"\nby = \"jessica79\"\ntimestamp = \"1978-09-24T13:44:40.210898\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.539337\"\nversion = \"v4.0\"\ntags = [ \"wait\", \"large\", \"business\", \"number\", \"young\",]\n",
"estimated_tokens": 261
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following JSON to XML:\n{\n \"timestamp\": \"2026-01-22T04:03:06.699723\",\n \"level\": \"ERROR\",\n \"message\": \"Research recently college street imagine memory discuss.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.699816\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"push\",\n \"cultural\",\n \"establish\",\n \"pull\",\n \"hit\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"cody95\",\n \"timestamp\": \"2015-02-04T15:33:29.237874\"\n }\n ]\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (timestamp, level, message...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:06.699723</timestamp>\n<level>ERROR</level>\n<message>Research recently college street imagine memory discuss.</message>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.699816</generated_at>\n<version>v2.0</version>\n<tags>push</tags>\n<tags>cultural</tags>\n<tags>establish</tags>\n<tags>pull</tags>\n<tags>hit</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>cody95</by>\n<timestamp>2015-02-04T15:33:29.237874</timestamp>\n</audit_log>\n</error_log>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "error_log",
"type": "conversion",
"prompt": "Convert the following JSON to XML:\n{\n \"timestamp\": \"2026-01-22T04:03:06.699723\",\n \"level\": \"ERROR\",\n \"message\": \"Research recently college street imagine memory discuss.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.699816\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"push\",\n \"cultural\",\n \"establish\",\n \"pull\",\n \"hit\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"cody95\",\n \"timestamp\": \"2015-02-04T15:33:29.237874\"\n }\n ]\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (timestamp, level, message...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:06.699723</timestamp>\n<level>ERROR</level>\n<message>Research recently college street imagine memory discuss.</message>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.699816</generated_at>\n<version>v2.0</version>\n<tags>push</tags>\n<tags>cultural</tags>\n<tags>establish</tags>\n<tags>pull</tags>\n<tags>hit</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>cody95</by>\n<timestamp>2015-02-04T15:33:29.237874</timestamp>\n</audit_log>\n</error_log>",
"estimated_tokens": 278
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Reformat the XML below into JSON:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>Ryan Livingston</student>\n<score>9</score>\n<grade>B</grade>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.775157</generated_at>\n<version>v2.0</version>\n<tags>provide</tags>\n<tags>finish</tags>\n<tags>civil</tags>\n<tags>always</tags>\n<tags>edge</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>hallen</by>\n<timestamp>2003-04-12T11:51:23.517029</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>pmelendez</by>\n<timestamp>1985-07-05T10:15:24.728379</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>hannahbrown</by>\n<timestamp>2003-01-04T01:29:14.132004</timestamp>\n</audit_log>\n</student_assessment>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (student, score, grade...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"student\": \"Ryan Livingston\",\n \"score\": 9,\n \"grade\": \"B\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.775157\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"provide\",\n \"finish\",\n \"civil\",\n \"always\",\n \"edge\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"hallen\",\n \"timestamp\": \"2003-04-12T11:51:23.517029\"\n },\n {\n \"action\": \"created\",\n \"by\": \"pmelendez\",\n \"timestamp\": \"1985-07-05T10:15:24.728379\"\n },\n {\n \"action\": \"created\",\n \"by\": \"hannahbrown\",\n \"timestamp\": \"2003-01-04T01:29:14.132004\"\n }\n ]\n}"
}
] |
{
"format": "json",
"complexity": "complex",
"schema": "student_assessment",
"type": "conversion",
"prompt": "Reformat the XML below into JSON:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>Ryan Livingston</student>\n<score>9</score>\n<grade>B</grade>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.775157</generated_at>\n<version>v2.0</version>\n<tags>provide</tags>\n<tags>finish</tags>\n<tags>civil</tags>\n<tags>always</tags>\n<tags>edge</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>hallen</by>\n<timestamp>2003-04-12T11:51:23.517029</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>pmelendez</by>\n<timestamp>1985-07-05T10:15:24.728379</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>hannahbrown</by>\n<timestamp>2003-01-04T01:29:14.132004</timestamp>\n</audit_log>\n</student_assessment>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (student, score, grade...) and a nesting depth of 3.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n{\n \"student\": \"Ryan Livingston\",\n \"score\": 9,\n \"grade\": \"B\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.775157\",\n \"version\": \"v2.0\",\n \"tags\": [\n \"provide\",\n \"finish\",\n \"civil\",\n \"always\",\n \"edge\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"hallen\",\n \"timestamp\": \"2003-04-12T11:51:23.517029\"\n },\n {\n \"action\": \"created\",\n \"by\": \"pmelendez\",\n \"timestamp\": \"1985-07-05T10:15:24.728379\"\n },\n {\n \"action\": \"created\",\n \"by\": \"hannahbrown\",\n \"timestamp\": \"2003-01-04T01:29:14.132004\"\n }\n ]\n}",
"estimated_tokens": 297
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Reformat the YAML below into TOML:\ncompany: Montoya and Sons\nrevenue: 966823\nprofit: 8052\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (company, revenue, profit) and a nesting depth of 1.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncompany = \"Montoya and Sons\"\nrevenue = 966823\nprofit = 8052\n"
}
] |
{
"format": "toml",
"complexity": "medium",
"schema": "financial_report",
"type": "conversion",
"prompt": "Reformat the YAML below into TOML:\ncompany: Montoya and Sons\nrevenue: 966823\nprofit: 8052\n",
"output": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (company, revenue, profit) and a nesting depth of 1.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\ncompany = \"Montoya and Sons\"\nrevenue = 966823\nprofit = 8052\n",
"estimated_tokens": 156
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Transform this data from TOML to XML:\nuser = \"sydneywhite\"\npost = \"Tonight available crime century voice enjoy. Until peace finally water believe cultural talk.\"\nlikes = 728\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>sydneywhite</user>\n<post>Tonight available crime century voice enjoy. Until peace finally water believe cultural talk.</post>\n<likes>728</likes>\n</social_media_post>"
}
] |
{
"format": "xml",
"complexity": "simple",
"schema": "social_media_post",
"type": "conversion",
"prompt": "Transform this data from TOML to XML:\nuser = \"sydneywhite\"\npost = \"Tonight available crime century voice enjoy. Until peace finally water believe cultural talk.\"\nlikes = 728\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>sydneywhite</user>\n<post>Tonight available crime century voice enjoy. Until peace finally water believe cultural talk.</post>\n<likes>728</likes>\n</social_media_post>",
"estimated_tokens": 200
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Create a CSV representation of contract."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The contract should contain a dictionary with 5 root fields (contract, parties, signed...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncontract,parties,signed,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nengineer robust portals,\"[\"\"Boyle Ltd\"\", \"\"Bauer, Knight and Hendricks\"\"]\",True,2026-01-22T04:03:06.355425,v1.0,\"[\"\"local\"\", \"\"image\"\", \"\"catch\"\", \"\"shoulder\"\", \"\"cup\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"nbennett\"\", \"\"timestamp\"\": \"\"1975-12-20T12:18:09.387573\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"batesmichelle\"\", \"\"timestamp\"\": \"\"1972-03-01T04:11:41.463965\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "contract",
"type": "generation",
"prompt": "Create a CSV representation of contract.",
"output": "Approach:\n1. Define the schema: The contract should contain a dictionary with 5 root fields (contract, parties, signed...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncontract,parties,signed,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nengineer robust portals,\"[\"\"Boyle Ltd\"\", \"\"Bauer, Knight and Hendricks\"\"]\",True,2026-01-22T04:03:06.355425,v1.0,\"[\"\"local\"\", \"\"image\"\", \"\"catch\"\", \"\"shoulder\"\", \"\"cup\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"nbennett\"\", \"\"timestamp\"\": \"\"1975-12-20T12:18:09.387573\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"batesmichelle\"\", \"\"timestamp\"\": \"\"1972-03-01T04:11:41.463965\"\"}]\"\r\n",
"estimated_tokens": 257
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Output structured data for prescription using JSON."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The prescription should contain a dictionary with 3 root fields (rx, drug, dosage) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"rx\": \"7d5d4256-d02d-49fd-a221-b9fd3fb569ac\",\n \"drug\": \"physical\",\n \"dosage\": \"10mg\"\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "prescription",
"type": "generation",
"prompt": "Output structured data for prescription using JSON.",
"output": "Approach:\n1. Define the schema: The prescription should contain a dictionary with 3 root fields (rx, drug, dosage) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"rx\": \"7d5d4256-d02d-49fd-a221-b9fd3fb569ac\",\n \"drug\": \"physical\",\n \"dosage\": \"10mg\"\n}",
"estimated_tokens": 158
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Generate product listing data in YAML format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct: mention\nprice: 34.67\nstock: 25\n"
}
] |
{
"format": "yaml",
"complexity": "medium",
"schema": "product_listing",
"type": "generation",
"prompt": "Generate product listing data in YAML format.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct: mention\nprice: 34.67\nstock: 25\n",
"estimated_tokens": 147
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Generate customer review data in CSV format."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser,rating,comment\r\nsmithmichelle,1,Education start season any seat her pretty.\r\n"
}
] |
{
"format": "csv",
"complexity": "simple",
"schema": "customer_review",
"type": "generation",
"prompt": "Generate customer review data in CSV format.",
"output": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser,rating,comment\r\nsmithmichelle,1,Education start season any seat her pretty.\r\n",
"estimated_tokens": 161
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Output structured data for contract using CSV."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncontract,parties,signed\r\nscale user-centric experiences,\"[\"\"Jenkins-Foster\"\", \"\"Chen Inc\"\"]\",True\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "contract",
"type": "generation",
"prompt": "Output structured data for contract using CSV.",
"output": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\ncontract,parties,signed\r\nscale user-centric experiences,\"[\"\"Jenkins-Foster\"\", \"\"Chen Inc\"\"]\",True\r\n",
"estimated_tokens": 165
}
|
[
{
"role": "system",
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON."
},
{
"role": "user",
"content": "Create a JSON representation of social media post."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"user\": \"donna33\",\n \"post\": \"Study call hot million. Particular film air TV.\\nNow fine campaign kind form. Keep per bit several ball buy movement never.\",\n \"likes\": 157\n}"
}
] |
{
"format": "json",
"complexity": "medium",
"schema": "social_media_post",
"type": "generation",
"prompt": "Create a JSON representation of social media post.",
"output": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n{\n \"user\": \"donna33\",\n \"post\": \"Study call hot million. Particular film air TV.\\nNow fine campaign kind form. Keep per bit several ball buy movement never.\",\n \"likes\": 157\n}",
"estimated_tokens": 180
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following TOML to XML:\nuser = \"douglas00\"\nrating = 3\ncomment = \"Consumer various by consider song.\"\n[[audit_log]]\naction = \"created\"\nby = \"nicholasjimenez\"\ntimestamp = \"1988-02-02T00:36:19.920888\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.572972\"\nversion = \"v5.0\"\ntags = [ \"avoid\", \"lose\", \"opportunity\", \"research\", \"would\",]\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>douglas00</user>\n<rating>3</rating>\n<comment>Consumer various by consider song.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:07.572972</generated_at>\n<version>v5.0</version>\n<tags>avoid</tags>\n<tags>lose</tags>\n<tags>opportunity</tags>\n<tags>research</tags>\n<tags>would</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>nicholasjimenez</by>\n<timestamp>1988-02-02T00:36:19.920888</timestamp>\n</audit_log>\n</customer_review>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "customer_review",
"type": "conversion",
"prompt": "Convert the following TOML to XML:\nuser = \"douglas00\"\nrating = 3\ncomment = \"Consumer various by consider song.\"\n[[audit_log]]\naction = \"created\"\nby = \"nicholasjimenez\"\ntimestamp = \"1988-02-02T00:36:19.920888\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.572972\"\nversion = \"v5.0\"\ntags = [ \"avoid\", \"lose\", \"opportunity\", \"research\", \"would\",]\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>douglas00</user>\n<rating>3</rating>\n<comment>Consumer various by consider song.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:07.572972</generated_at>\n<version>v5.0</version>\n<tags>avoid</tags>\n<tags>lose</tags>\n<tags>opportunity</tags>\n<tags>research</tags>\n<tags>would</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>nicholasjimenez</by>\n<timestamp>1988-02-02T00:36:19.920888</timestamp>\n</audit_log>\n</customer_review>",
"estimated_tokens": 271
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Output structured data for product_listing using TOML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct = \"why\"\nprice = 49.26\nstock = 4\n"
}
] |
{
"format": "toml",
"complexity": "simple",
"schema": "product_listing",
"type": "generation",
"prompt": "Output structured data for product_listing using TOML.",
"output": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nproduct = \"why\"\nprice = 49.26\nstock = 4\n",
"estimated_tokens": 145
}
|
[
{
"role": "system",
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML."
},
{
"role": "user",
"content": "Output structured data for api_specification using TOML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 5 root fields (endpoint, method, responses...) and a nesting depth of 3.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nendpoint = \"/api/v1/users\"\nmethod = \"GET\"\n[[audit_log]]\naction = \"created\"\nby = \"bparrish\"\ntimestamp = \"2007-06-13T18:46:35.455145\"\n\n[responses]\n200 = \"OK\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.471586\"\nversion = \"v3.0\"\ntags = [ \"peace\", \"little\", \"early\", \"necessary\", \"building\",]\n"
}
] |
{
"format": "toml",
"complexity": "complex",
"schema": "api_specification",
"type": "generation",
"prompt": "Output structured data for api_specification using TOML.",
"output": "Approach:\n1. Define the schema: The api_specification should contain a dictionary with 5 root fields (endpoint, method, responses...) and a nesting depth of 3.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nendpoint = \"/api/v1/users\"\nmethod = \"GET\"\n[[audit_log]]\naction = \"created\"\nby = \"bparrish\"\ntimestamp = \"2007-06-13T18:46:35.455145\"\n\n[responses]\n200 = \"OK\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.471586\"\nversion = \"v3.0\"\ntags = [ \"peace\", \"little\", \"early\", \"necessary\", \"building\",]\n",
"estimated_tokens": 211
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Transform this data from XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<api_specification>\n<endpoint>/api/v1/users</endpoint>\n<method>GET</method>\n<responses>\n<_200>OK</_200>\n</responses>\n</api_specification>"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nendpoint,method,responses.200\r\n/api/v1/users,GET,OK\r\n"
}
] |
{
"format": "csv",
"complexity": "medium",
"schema": "api_specification",
"type": "conversion",
"prompt": "Transform this data from XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<api_specification>\n<endpoint>/api/v1/users</endpoint>\n<method>GET</method>\n<responses>\n<_200>OK</_200>\n</responses>\n</api_specification>",
"output": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (endpoint, method, responses) and a nesting depth of 2.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nendpoint,method,responses.200\r\n/api/v1/users,GET,OK\r\n",
"estimated_tokens": 161
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Transform this data from CSV to XML:\ntxn,amount,status\r\n384d0756-3426-42f4-9005-846121adb42a,92.57,completed\r\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<transaction_record>\n<txn>384d0756-3426-42f4-9005-846121adb42a</txn>\n<amount>92.57</amount>\n<status>completed</status>\n</transaction_record>"
}
] |
{
"format": "xml",
"complexity": "medium",
"schema": "transaction_record",
"type": "conversion",
"prompt": "Transform this data from CSV to XML:\ntxn,amount,status\r\n384d0756-3426-42f4-9005-846121adb42a,92.57,completed\r\n",
"output": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 3 root fields (txn, amount, status) and a nesting depth of 1.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<transaction_record>\n<txn>384d0756-3426-42f4-9005-846121adb42a</txn>\n<amount>92.57</amount>\n<status>completed</status>\n</transaction_record>",
"estimated_tokens": 188
}
|
[
{
"role": "system",
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV."
},
{
"role": "user",
"content": "Output structured data for social_media_post using CSV."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser,post,likes,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nrandybyrd,Season establish say participant western from. Drug few enjoy bad care and.,231,2026-01-22T04:03:07.307816,v3.0,\"[\"\"floor\"\", \"\"result\"\", \"\"important\"\", \"\"change\"\", \"\"section\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"nmurphy\"\", \"\"timestamp\"\": \"\"1987-11-11T21:03:15.299084\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"phillipsjustin\"\", \"\"timestamp\"\": \"\"1973-06-14T04:21:13.791233\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"nataliebryant\"\", \"\"timestamp\"\": \"\"1992-01-10T21:38:49.755124\"\"}]\"\r\n"
}
] |
{
"format": "csv",
"complexity": "complex",
"schema": "social_media_post",
"type": "generation",
"prompt": "Output structured data for social_media_post using CSV.",
"output": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nuser,post,likes,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\r\nrandybyrd,Season establish say participant western from. Drug few enjoy bad care and.,231,2026-01-22T04:03:07.307816,v3.0,\"[\"\"floor\"\", \"\"result\"\", \"\"important\"\", \"\"change\"\", \"\"section\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"nmurphy\"\", \"\"timestamp\"\": \"\"1987-11-11T21:03:15.299084\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"phillipsjustin\"\", \"\"timestamp\"\": \"\"1973-06-14T04:21:13.791233\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"nataliebryant\"\", \"\"timestamp\"\": \"\"1992-01-10T21:38:49.755124\"\"}]\"\r\n",
"estimated_tokens": 284
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Create a XML representation of error log."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 5 root fields (timestamp, level, message...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:05.653726</timestamp>\n<level>ERROR</level>\n<message>Father church subject time gun the article free.</message>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.653853</generated_at>\n<version>v1.0</version>\n<tags>matter</tags>\n<tags>prevent</tags>\n<tags>behavior</tags>\n<tags>part</tags>\n<tags>meet</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>welliott</by>\n<timestamp>2025-08-20T04:27:40.928504</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>gthomas</by>\n<timestamp>2020-03-03T02:31:20.451984</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>jmolina</by>\n<timestamp>1970-06-05T20:48:12.968662</timestamp>\n</audit_log>\n</error_log>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "error_log",
"type": "generation",
"prompt": "Create a XML representation of error log.",
"output": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 5 root fields (timestamp, level, message...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:05.653726</timestamp>\n<level>ERROR</level>\n<message>Father church subject time gun the article free.</message>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.653853</generated_at>\n<version>v1.0</version>\n<tags>matter</tags>\n<tags>prevent</tags>\n<tags>behavior</tags>\n<tags>part</tags>\n<tags>meet</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>welliott</by>\n<timestamp>2025-08-20T04:27:40.928504</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>gthomas</by>\n<timestamp>2020-03-03T02:31:20.451984</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>jmolina</by>\n<timestamp>1970-06-05T20:48:12.968662</timestamp>\n</audit_log>\n</error_log>",
"estimated_tokens": 328
}
|
[
{
"role": "system",
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML."
},
{
"role": "user",
"content": "Convert the following JSON to XML:\n{\n \"user\": \"sjohnson\",\n \"rating\": 4,\n \"comment\": \"And keep simply.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.957681\",\n \"version\": \"v4.0\",\n \"tags\": [\n \"wide\",\n \"compare\",\n \"evening\",\n \"people\",\n \"program\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"erin32\",\n \"timestamp\": \"1989-07-18T05:45:15.715520\"\n },\n {\n \"action\": \"created\",\n \"by\": \"theresamunoz\",\n \"timestamp\": \"2012-01-25T01:26:18.312616\"\n }\n ]\n}"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>sjohnson</user>\n<rating>4</rating>\n<comment>And keep simply.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.957681</generated_at>\n<version>v4.0</version>\n<tags>wide</tags>\n<tags>compare</tags>\n<tags>evening</tags>\n<tags>people</tags>\n<tags>program</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>erin32</by>\n<timestamp>1989-07-18T05:45:15.715520</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>theresamunoz</by>\n<timestamp>2012-01-25T01:26:18.312616</timestamp>\n</audit_log>\n</customer_review>"
}
] |
{
"format": "xml",
"complexity": "complex",
"schema": "customer_review",
"type": "conversion",
"prompt": "Convert the following JSON to XML:\n{\n \"user\": \"sjohnson\",\n \"rating\": 4,\n \"comment\": \"And keep simply.\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:06.957681\",\n \"version\": \"v4.0\",\n \"tags\": [\n \"wide\",\n \"compare\",\n \"evening\",\n \"people\",\n \"program\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"erin32\",\n \"timestamp\": \"1989-07-18T05:45:15.715520\"\n },\n {\n \"action\": \"created\",\n \"by\": \"theresamunoz\",\n \"timestamp\": \"2012-01-25T01:26:18.312616\"\n }\n ]\n}",
"output": "Approach:\n1. Analyze the input JSON structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>sjohnson</user>\n<rating>4</rating>\n<comment>And keep simply.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.957681</generated_at>\n<version>v4.0</version>\n<tags>wide</tags>\n<tags>compare</tags>\n<tags>evening</tags>\n<tags>people</tags>\n<tags>program</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>erin32</by>\n<timestamp>1989-07-18T05:45:15.715520</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>theresamunoz</by>\n<timestamp>2012-01-25T01:26:18.312616</timestamp>\n</audit_log>\n</customer_review>",
"estimated_tokens": 294
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Transform this data from TOML to YAML:\nuser = \"melissa68\"\npost = \"Eye middle each. Phone even decade whole along.\\nNotice run conference property top far. Million manage it quality child contain summer.\"\nlikes = 151\n[[audit_log]]\naction = \"created\"\nby = \"richardmcclure\"\ntimestamp = \"1996-06-12T16:54:51.177304\"\n\n[[audit_log]]\naction = \"created\"\nby = \"pattersonlisa\"\ntimestamp = \"2025-07-13T20:14:11.229115\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.462980\"\nversion = \"v1.0\"\ntags = [ \"minute\", \"mother\", \"animal\", \"food\", \"poor\",]\n"
},
{
"role": "assistant",
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser: melissa68\npost: 'Eye middle each. Phone even decade whole along.\n\n Notice run conference property top far. Million manage it quality child contain\n summer.'\nlikes: 151\nmeta_info:\n generated_at: '2026-01-22T04:03:07.462980'\n version: v1.0\n tags:\n - minute\n - mother\n - animal\n - food\n - poor\naudit_log:\n- action: created\n by: richardmcclure\n timestamp: '1996-06-12T16:54:51.177304'\n- action: created\n by: pattersonlisa\n timestamp: '2025-07-13T20:14:11.229115'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "social_media_post",
"type": "conversion",
"prompt": "Transform this data from TOML to YAML:\nuser = \"melissa68\"\npost = \"Eye middle each. Phone even decade whole along.\\nNotice run conference property top far. Million manage it quality child contain summer.\"\nlikes = 151\n[[audit_log]]\naction = \"created\"\nby = \"richardmcclure\"\ntimestamp = \"1996-06-12T16:54:51.177304\"\n\n[[audit_log]]\naction = \"created\"\nby = \"pattersonlisa\"\ntimestamp = \"2025-07-13T20:14:11.229115\"\n\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.462980\"\nversion = \"v1.0\"\ntags = [ \"minute\", \"mother\", \"animal\", \"food\", \"poor\",]\n",
"output": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\n\nOutput:\nuser: melissa68\npost: 'Eye middle each. Phone even decade whole along.\n\n Notice run conference property top far. Million manage it quality child contain\n summer.'\nlikes: 151\nmeta_info:\n generated_at: '2026-01-22T04:03:07.462980'\n version: v1.0\n tags:\n - minute\n - mother\n - animal\n - food\n - poor\naudit_log:\n- action: created\n by: richardmcclure\n timestamp: '1996-06-12T16:54:51.177304'\n- action: created\n by: pattersonlisa\n timestamp: '2025-07-13T20:14:11.229115'\n",
"estimated_tokens": 263
}
|
[
{
"role": "system",
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML."
},
{
"role": "user",
"content": "Output structured data for news_article using YAML."
},
{
"role": "assistant",
"content": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 5 root fields (headline, body, author...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nheadline: Behavior yet ask difficult PM.\nbody: Though staff head worker other call. Campaign call alone carry former. Live\n teach fast never be woman available.\nauthor: Karen Bennett\nmeta_info:\n generated_at: '2026-01-22T04:03:05.321791'\n version: v2.0\n tags:\n - budget\n - it\n - sea\n - sit\n - woman\naudit_log:\n- action: created\n by: wardkaitlyn\n timestamp: '2022-10-07T13:11:05.072118'\n- action: created\n by: eparsons\n timestamp: '2011-07-09T12:56:15.657947'\n"
}
] |
{
"format": "yaml",
"complexity": "complex",
"schema": "news_article",
"type": "generation",
"prompt": "Output structured data for news_article using YAML.",
"output": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 5 root fields (headline, body, author...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\n\nOutput:\nheadline: Behavior yet ask difficult PM.\nbody: Though staff head worker other call. Campaign call alone carry former. Live\n teach fast never be woman available.\nauthor: Karen Bennett\nmeta_info:\n generated_at: '2026-01-22T04:03:05.321791'\n version: v2.0\n tags:\n - budget\n - it\n - sea\n - sit\n - woman\naudit_log:\n- action: created\n by: wardkaitlyn\n timestamp: '2022-10-07T13:11:05.072118'\n- action: created\n by: eparsons\n timestamp: '2011-07-09T12:56:15.657947'\n",
"estimated_tokens": 255
}
|
Subsets and Splits
Format and Complexity Counts
Groups training examples by their format and complexity metadata to reveal patterns in dataset structure and potentially identify undersampled combinations that could inform data balancing strategies.