| | --- |
| | license: mit |
| | --- |
| | |
| | # CAMeLBERT-CATiB-parser |
| |
|
| | ## Model description |
| | The **CAMeLBERT-CATiB-parser** is a neural dependency parsing model for Arabic text, specifically designed for the CATiB dependency formalism. |
| | It is based on the Biaffine Attention Dependency Parsing model introduced by [Dozat and Manning (2017)](https://arxiv.org/pdf/1611.01734.pdf) and implemented in |
| | [SuPar](https://github.com/yzhangcs/parser), which has been shown to be very effective for dependency parsing in many languages. |
| | The model is trained on the CamelTB and PATB combined train sets, which are both large Arabic corpora. |
| | The model uses a CamelBERT-MSA word embedding layer, which is a pre-trained language model that has been trained on a massive dataset of Arabic text. |
| | The model was introduced in our paper "CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic". |
| | The paper describes the model in detail and evaluates its performance on various Arabic dependency parsing tasks. |
| |
|
| | ## Intended uses |
| | The CAMeLBERT-CATiB-parser is shipped with the [CAMeLParser](https://github.com/CAMeL-Lab/camel_parser) as one of the default parsing models, |
| | and can be selected when parsing texts using the CATiB formalism. |
| |
|
| | ## Citation |
| | ```bibtex |
| | @inproceedings{Elshabrawy:2023:camelparser, |
| | title = "{CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic}", |
| | author = {Ahmed Elshabrawy and |
| | Muhammed AbuOdeh and |
| | Go Inoue and |
| | Nizar Habash} , |
| | booktitle = {Proceedings of The First Arabic Natural Language Processing Conference (ArabicNLP 2023)}, |
| | year = "2023" |
| | } |
| | ``` |
