Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting an Under-Resourced Language
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866929615889498112 |
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| author | Riabi, Arij Mahamdi, Menel Seddah, Djamé |
| author_facet | Riabi, Arij Mahamdi, Menel Seddah, Djamé |
| contents | In this paper we address the scarcity of annotated data for NArabizi, a Romanized form of North African Arabic used mostly on social media, which poses challenges for Natural Language Processing (NLP). We introduce an enriched version of NArabizi Treebank (Seddah et al., 2020) with three main contributions: the addition of two novel annotation layers (named entity recognition and offensive language detection) and a re-annotation of the tokenization, morpho-syntactic and syntactic layers that ensure annotation consistency. Our experimental results, using different tokenization schemes, showcase the value of our contributions and highlight the impact of working with non-gold tokenization for NER and dependency parsing. To facilitate future research, we make these annotations publicly available. Our enhanced NArabizi Treebank paves the way for creating sophisticated language models and NLP tools for this under-represented language. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_14866 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting an Under-Resourced Language Riabi, Arij Mahamdi, Menel Seddah, Djamé Computation and Language In this paper we address the scarcity of annotated data for NArabizi, a Romanized form of North African Arabic used mostly on social media, which poses challenges for Natural Language Processing (NLP). We introduce an enriched version of NArabizi Treebank (Seddah et al., 2020) with three main contributions: the addition of two novel annotation layers (named entity recognition and offensive language detection) and a re-annotation of the tokenization, morpho-syntactic and syntactic layers that ensure annotation consistency. Our experimental results, using different tokenization schemes, showcase the value of our contributions and highlight the impact of working with non-gold tokenization for NER and dependency parsing. To facilitate future research, we make these annotations publicly available. Our enhanced NArabizi Treebank paves the way for creating sophisticated language models and NLP tools for this under-represented language. |
| title | Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting an Under-Resourced Language |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2306.14866 |