Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
name: string
description: string
created_at: timestamp[s]
n_records: int64
records_file: string
records_sha256: string
category_counts: struct<thai_reading_comprehension: int64, thai_civics_history_science: int64, thai_math_word_problem (... 105 chars omitted)
child 0, thai_reading_comprehension: int64
child 1, thai_civics_history_science: int64
child 2, thai_math_word_problem: int64
child 3, negation_exception: int64
child 4, multi_hop_short_context_qa: int64
child 5, thai_instruction_following: int64
task_type_counts: struct<thai_mcq_reasoning_sft: int64, thai_instruction_reasoning_sft: int64>
child 0, thai_mcq_reasoning_sft: int64
child 1, thai_instruction_reasoning_sft: int64
answer_counts: struct<a: int64, b: int64, c: int64, d: int64, e: int64, non_mcq: int64>
child 0, a: int64
child 1, b: int64
child 2, c: int64
child 3, d: int64
child 4, e: int64
child 5, non_mcq: int64
target_skills: list<item: string>
child 0, item: string
provenance: struct<authoring: string, external_sources: string, benchmark_files_read: bool, gold_answers_read: b (... 194 chars omitted)
child 0, authoring: string
child 1, external_sources: string
child 2, benchmark_files_read: bool
child 3, gold_answers_read: bool
child 4, model_predictions_used: bool
child 5, benchmark_prompt_gold_answer_or_sample_used: bool
child 6, benchmark_text_contamination_scan_performed: bool
child 7, benchmark_text_contamination_scan_omitted_reason: string
campaign_constraints: struct<target_model_name: string, developer: string, developer_th: string, final_model_max_params: s (... 217 chars omitted)
child 0, target_model_name: string
child 1, developer: string
child 2, developer_th: string
child 3, final_model_max_params: string
child 4, not_thai_family_base_model: bool
child 5, real_greedy_single_model_eval_only: bool
child 6, no_bon: bool
child 7, no_self_consistency: bool
child 8, no_routing: bool
child 9, no_ensemble: bool
child 10, no_verifier_selection: bool
child 11, no_benchmark_leakage: bool
format_audit: struct<n_issues: int64, audit_file: string>
child 0, n_issues: int64
child 1, audit_file: string
n_issues: int64
issues: list<item: null>
child 0, item: null
notes: string
to
{'name': Value('string'), 'n_records': Value('int64'), 'n_issues': Value('int64'), 'issues': List(Value('null')), 'category_counts': {'thai_reading_comprehension': Value('int64'), 'thai_civics_history_science': Value('int64'), 'thai_math_word_problem': Value('int64'), 'negation_exception': Value('int64'), 'multi_hop_short_context_qa': Value('int64'), 'thai_instruction_following': Value('int64')}, 'answer_counts': {'a': Value('int64'), 'b': Value('int64'), 'c': Value('int64'), 'd': Value('int64'), 'e': Value('int64'), 'non_mcq': Value('int64')}, 'notes': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
name: string
description: string
created_at: timestamp[s]
n_records: int64
records_file: string
records_sha256: string
category_counts: struct<thai_reading_comprehension: int64, thai_civics_history_science: int64, thai_math_word_problem (... 105 chars omitted)
child 0, thai_reading_comprehension: int64
child 1, thai_civics_history_science: int64
child 2, thai_math_word_problem: int64
child 3, negation_exception: int64
child 4, multi_hop_short_context_qa: int64
child 5, thai_instruction_following: int64
task_type_counts: struct<thai_mcq_reasoning_sft: int64, thai_instruction_reasoning_sft: int64>
child 0, thai_mcq_reasoning_sft: int64
child 1, thai_instruction_reasoning_sft: int64
answer_counts: struct<a: int64, b: int64, c: int64, d: int64, e: int64, non_mcq: int64>
child 0, a: int64
child 1, b: int64
child 2, c: int64
child 3, d: int64
child 4, e: int64
child 5, non_mcq: int64
target_skills: list<item: string>
child 0, item: string
provenance: struct<authoring: string, external_sources: string, benchmark_files_read: bool, gold_answers_read: b (... 194 chars omitted)
child 0, authoring: string
child 1, external_sources: string
child 2, benchmark_files_read: bool
child 3, gold_answers_read: bool
child 4, model_predictions_used: bool
child 5, benchmark_prompt_gold_answer_or_sample_used: bool
child 6, benchmark_text_contamination_scan_performed: bool
child 7, benchmark_text_contamination_scan_omitted_reason: string
campaign_constraints: struct<target_model_name: string, developer: string, developer_th: string, final_model_max_params: s (... 217 chars omitted)
child 0, target_model_name: string
child 1, developer: string
child 2, developer_th: string
child 3, final_model_max_params: string
child 4, not_thai_family_base_model: bool
child 5, real_greedy_single_model_eval_only: bool
child 6, no_bon: bool
child 7, no_self_consistency: bool
child 8, no_routing: bool
child 9, no_ensemble: bool
child 10, no_verifier_selection: bool
child 11, no_benchmark_leakage: bool
format_audit: struct<n_issues: int64, audit_file: string>
child 0, n_issues: int64
child 1, audit_file: string
n_issues: int64
issues: list<item: null>
child 0, item: null
notes: string
to
{'name': Value('string'), 'n_records': Value('int64'), 'n_issues': Value('int64'), 'issues': List(Value('null')), 'category_counts': {'thai_reading_comprehension': Value('int64'), 'thai_civics_history_science': Value('int64'), 'thai_math_word_problem': Value('int64'), 'negation_exception': Value('int64'), 'multi_hop_short_context_qa': Value('int64'), 'thai_instruction_following': Value('int64')}, 'answer_counts': {'a': Value('int64'), 'b': Value('int64'), 'c': Value('int64'), 'd': Value('int64'), 'e': Value('int64'), 'non_mcq': Value('int64')}, 'notes': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Kanitakorn v57 Clean Thai Exam Skills Seed
Synthetic SFT sidecar candidate for the Kanitakorn campaign.
Contents
records.jsonl: 150 Thai chat SFT records in messages format.manifest.json: counts, provenance, and campaign constraints.audit_format.json: local format and final-answer audit.build_dataset.py: deterministic generator for this pack.
Source Policy
This pack is hand-authored from deterministic synthetic templates. It does not read, copy, paraphrase, or derive from ThaiExam benchmark prompts, gold labels, sample rows, eval inputs, eval predictions, or model outputs. No web scraping or external corpus was used.
Skill Coverage
- Thai reading comprehension with evidence and bounded inference.
- Thai civics/history/science/common-knowledge reasoning.
- Thai math word problems with unit-aware arithmetic.
- Negation and exception-boundary interpretation.
- Multi-hop short-context QA.
- Thai instruction following with explicit constraints.
Contamination Guard
- Benchmark files read: no.
- Gold answers read: no.
- Model predictions used as training rows: no.
- Benchmark text contamination scan: intentionally omitted because loading benchmark text would violate this task's non-leakage constraint.
- Format audit issues: 0.
Final model claims must remain real greedy single-model results only: no BoN, self-consistency, routing, ensemble, or verifier selection.
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