Lemmatization as a Classification Task: Results from Arabic across Multiple Genres

What it is about

Arabic lemmatization is hard because the orthography drops vowels, so one written word has several lemma, POS and gloss readings. The authors frame lemmatization as choosing one Lemma-POS-Gloss (LPG) label from the analyser's candidates, using either a classifier over about 18,000 LPG classes or a clustering of the whole 49K-entry LPG space into about 2,000 semantic clusters. They also build a new multi-genre test set (from the BAREC corpus: poetry, novels, children's stories and others) and align six existing Arabic datasets to one lemma convention. The best setups, clustering and classification with a POS tagger filter, beat the tagger baseline on every test set, with significant gains (McNemar, p < 0.05); the tagger alone cuts the analyser's average of about 15 analyses per word to 1.3, and the LPG level keeps only 2.7 analyses on average before the tagger. A character-level seq2seq model is competitive but hallucinates forms.

Ideas

• I1. Use the lemma-POS-gloss triple as the unit of the Hebrew dictionary (macula dict): store the three together and measure how many candidates per word remain after the POS tagger, the same way the paper's Table 2 does for Arabic.
• I2. A deterministic gloss-overlap rule for ambiguous readings: among candidate senses of a word, prefer the one whose gloss shares content words with the English gloss words already in the frame. It is a table lookup, not the paper's neural cosine similarity.
• I3. Hold out one genre (for example, the late or narrative texts) as a test set for the lemma rules, and report accuracy per genre rather than one overall number.

For Mova

I1 goes into The lexicon and tools/macula (macula dict). I2 is a rule for the prag and world senses, tested first on Hebrew glosses. I3 is a test set for the lemma rules in tools/hbo; the genre split follows the Hebrew layers in 11. Mishnaic Hebrew (hbo-x-mishnaic).

Topics: Part-of-speech tagging

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.18653/v1/2025.emnlp-main.1525 · arXiv 2506.18399

@inproceedings{saeed2025lemmatization,
  title = {{Lemmatization as a Classification Task: Results from Arabic across Multiple Genres}},
  author = {Saeed, Mostafa and Habash, Nizar},
  booktitle = {Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing},
  year = {2025},
  doi = {10.18653/v1/2025.emnlp-main.1525},
  eprint = {2506.18399},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.18653/v1/2025.emnlp-main.1525}
}

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