Shaltiel Shmidman


2020

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A Novel Challenge Set for Hebrew Morphological Disambiguation and Diacritics Restoration
Avi Shmidman | Joshua Guedalia | Shaltiel Shmidman | Moshe Koppel | Reut Tsarfaty
Findings of the Association for Computational Linguistics: EMNLP 2020

One of the primary tasks of morphological parsers is the disambiguation of homographs. Particularly difficult are cases of unbalanced ambiguity, where one of the possible analyses is far more frequent than the others. In such cases, there may not exist sufficient examples of the minority analyses in order to properly evaluate performance, nor to train effective classifiers. In this paper we address the issue of unbalanced morphological ambiguities in Hebrew. We offer a challenge set for Hebrew homographs — the first of its kind — containing substantial attestation of each analysis of 21 Hebrew homographs. We show that the current SOTA of Hebrew disambiguation performs poorly on cases of unbalanced ambiguity. Leveraging our new dataset, we achieve a new state-of-the-art for all 21 words, improving the overall average F1 score from 0.67 to 0.95. Our resulting annotated datasets are made publicly available for further research.

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Nakdan: Professional Hebrew Diacritizer
Avi Shmidman | Shaltiel Shmidman | Moshe Koppel | Yoav Goldberg
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

We present a system for automatic diacritization of Hebrew Text. The system combines modern neural models with carefully curated declarative linguistic knowledge and comprehensive manually constructed tables and dictionaries. Besides providing state of the art diacritization accuracy, the system also supports an interface for manual editing and correction of the automatic output, and has several features which make it particularly useful for preparation of scientific editions of historical Hebrew texts. The system supports Modern Hebrew, Rabbinic Hebrew and Poetic Hebrew. The system is freely accessible for all use at http://nakdanpro.dicta.org.il