Noun Phrase Chunking in Hebrew: Influence of Lexical and Morphological Features

Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the ACL, pages 689–696, Sydney, July 2006. c⃝2006 Association for Computational Linguistics Noun Phrase Chunking in Hebrew Influence of Lexical and Morphological Features Yoav Goldberg and Meni Adler and Michael Elhadad Computer Science Department Ben Gurion University of the Negev P.O.B 653 Be'er Sheva 84105, Israel {yoavg,adlerm,elhadad}@cs.bgu.ac.il Abstract We present a method for Noun Phrase chunking in Hebrew. We show that the traditional definition of base-NPs as non- recursive noun phrases does not apply in Hebrew, and propose an alternative defi- nition of Simple NPs. We review syntac- tic properties of Hebrew related to noun phrases, which indicate that the task of Hebrew SimpleNP chunking is harder than base-NP chunking in English. As a confirmation, we apply methods known to work well for English to Hebrew data. These methods give low results (F from 76 to 86) in Hebrew. We then discuss our method, which applies SVM induction over lexical and morphological features. Morphological features improve the av- erage precision by ~0.5%, recall by ~1%, and F-measure by ~0.75, resulting in a system with average performance of 93% precision, 93.4% recall and 93.2 F- measure.* 1 Introduction Modern Hebrew is an agglutinative Semitic lan- guage, with rich morphology. Like most other non-European languages, it lacks NLP resources and tools, and specifically there are currently no available syntactic parsers for Hebrew. We ad- dress the task of NP chunking in Hebrew as a * This work was funded by the Israel Ministry of Sci- ence and Technology under the auspices of the Knowledge Center for Processing Hebrew. Addi- tional funding was provided by the Lynn and William Frankel Center for Computer Sciences. first step to fulfill the need for such tools. We also illustrate how this task can successfully be approached with little resource requirements, and indicate how the method is applicable to other resource-scarce languages. NP chunking is the task of labelling noun phrases in natural language text. The input to this task is free text with part-of-speech tags. The output is the same text with brackets around base noun phrases. A base noun phrase is an NP which does not contain another NP (it is not re- cursive). NP chunking is the basis for many other NLP tasks such as shallow parsing, argu- ment structure identification, and information extraction We first realize that the definition of base-NPs must be adapted to the case of Hebrew (and probably other Semitic languages as well) to cor- rectly handle its syntactic nature. We propose such a definition, which we call simple NPs and assess the difficulty of chunking such NPs by applying methods that perform well in English to Hebrew data. While the syntactic problem in Hebrew is indeed more difficult than in English, morphological clues do provide additional hints, which we exploit using an SVM learning method. The resulting method reaches perform- ance in Hebrew comparable to the best results published in English. 2 Previous Work Text …

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