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Out-of-Domain Dependency Parsing for Dialects of Arabic: A Case Study

What it is about

No syntactically annotated treebank exists for Arabic dialects, so the parser is trained on the CATiB MSA treebank and tested on dialect sentences: a test set of 800 parallel sentences from MADAR (Gulf, Levantine, Egyptian and Maghrebi). The authors annotate the test set themselves, for two hard constructions: idafa (noun-noun possessives, including the dialectal prepositional form) and coordination with "wa". The out-of-domain baseline is poor, with LAS between 23.2 (Maghrebi) and 27.5 (Levantine). Shortening the training sentences to 15 words or fewer adds about 2–3 points, and removing MSA sentences that begin with a sentential "wa" helps coordination and idafa too. The best results come from adding the 2,000-sentence MSA part of MADAR to training. Dialectal embeddings give only small, inconsistent gains, so the authors conclude that genre differences hurt more than dialect differences.

Ideas

For Mova

I1 and I2 are data-selection rules for the parser training of gparse. I2 also matters for the waw-clause structure in Syntax: the clause and the sentence. I3 is a test set: a per-construction score for idafa (construct chains) and coordination in treebanks/hbo/ptnk and treebanks/ar. The genre finding is a warning for the Hebrew test sets: a gain on one genre does not show up on another.

Topics: Dependency parsing · Treebanks

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.18653/v1/2024.arabicnlp-1.16

@inproceedings{mokh2024out,
  title = {{Out-of-Domain Dependency Parsing for Dialects of Arabic: A Case Study}},
  author = {Mokh, Noor Abo and Dakota, Daniel and Kübler, Sandra},
  booktitle = {Proceedings of the Second Arabic Natural Language Processing Conference},
  year = {2024},
  doi = {10.18653/v1/2024.arabicnlp-1.16},
  url = {https://doi.org/10.18653/v1/2024.arabicnlp-1.16}
}

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