A Comprehensive NLP System for Modern Standard Arabic and Modern Hebrew
What it is about
The paper describes Morfix, a commercial Hebrew system from Melingo with morphological analysis, context-sensitive lemmatization, vocalization, text-to-phoneme conversion and a syntax-based prosody model, and its extension to Modern Standard Arabic. The authors argue that the two languages share one architecture: the same lemma database, rule databases and a single notion of AGREEMENT, with language-specific rules only where needed. A lemma is the least marked inflectional form, not the root; roots group lemmas into "word families" on top. About 70 million inflected forms are generated from lemma records and rules, with lexicographer exceptions. The ambiguity comes from homographic forms, clitic combinations and unvocalized spelling. The figures are the vendor's own, without a public test set: for Hebrew, above 98% of tokens get the top-scored lemma right, 1–2% of web words stay unanalysed, and the system runs at about 10,000 words per second on an 800 MHz machine.
Ideas
- I1. A lemma policy for the lexicon: lemma = least marked form, a different part of speech means a different lemma, and the root is an optional grouping key. Use it in 8. Lexicon and register; the root grouping could also fill the gap that
macula dicthas no roots yet. - I2. Verb-derived nominals are ambiguous with copular clauses (the paper's
axi shomer, "my brother is a guard" or "my brother guards"). Build a minimal-pair test for 05. The verb: system, binyanim, tense and use and 05b. Verb paradigms: the strong verb in seven binyanim and the weak roots, where the cue is the presence of an auxiliary or a tense marker in the clause. - I3. Spelling alternatives (Ktiv Haser against Ktiv Male) as rules that generate variants from the lexical form, not as stored strings. The paper reports that the semi-vocalized system adds about 25% to the token count. The rule table belongs in 2. Script and spelling.
- I4. Report two numbers for any Hebrew lemma stage: top-score lemma accuracy and the rate of unanalysed tokens, both on a held-out corpus. These are the gates we would use.
For Mova
I1 goes into 8. Lexicon and register. I2 is a test for 05. The verb: system, binyanim, tense and use and 05b. Verb paradigms: the strong verb in seven binyanim and the weak roots. I3 goes into 2. Script and spelling. I4 is a measurement rule for 12. Mova and Modern Hebrew: where it stands, what it would need.
Cite
@inproceedings{kamir2002comprehensive,
title = {{A Comprehensive NLP System for Modern Standard Arabic and Modern Hebrew}},
author = {Kamir, Dror and Soreq, Naama and Neeman, Yoni},
booktitle = {Proceedings of the ACL-02 Workshop on Computational Approaches to Semitic Languages},
year = {2002},
doi = {10.3115/1118637.1118646},
url = {https://doi.org/10.3115/1118637.1118646}
}References
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