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Tagging a Hebrew Corpus: the Case of Participles

What it is about

The authors build a part-of-speech and morphology corpus of Modern Hebrew news (about 40M tokens, with a 200K-token sample tagged by hand). Their guidelines start from dictionaries and the Penn Treebank scheme, and they revise them as taggers disagree. The main problem is the beinoni (participle) form, which shares properties of nouns, adjectives and verbs. Eight Hebrew sources assign it almost systematically different verb, noun or adjective tags. The authors add a separate participle tag, defined by morphological and syntactic tests: a present-verb use is tense-bound and needs an explicit subject, while noun and adjective uses take no tense and can carry a possessive suffix or a modifier. Disagreement between taggers fell from about 20% to 3% after a few rounds of revision. The tag also helped a syntactic chunker. The part of the paper read gives agreement figures and the tests, not a single accuracy headline.

Ideas

For Mova

I1 goes into 11. Modern Hebrew in Universal Dependencies and 05. The verb: system, binyanim, tense and use. I2 is a rule set for 05b. Verb paradigms: the strong verb in seven binyanim and the weak roots and the frame reader. I3 is a test set for the Modern Hebrew lexicon, 8. Lexicon and register.

Topics: Part-of-speech tagging

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.63317/5nvswopp4v97

@inproceedings{adler2008tagging,
  title = {{Tagging a Hebrew Corpus: the Case of Participles}},
  author = {Adler, Meni and Netzer, Yael and Goldberg, Yoav and Gabay, David and Elhadad, Michael},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  doi = {10.63317/5nvswopp4v97},
  url = {https://doi.org/10.63317/5nvswopp4v97}
}

References

23 references, 4 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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  15. Mark Van Mol. 2002. The semi-automatic tagging of arabic corpora. In Arabic Language Resources and Evaluation - Status and Prospects Workshop, LREC. find
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