TAILIEUCHUNG - Báo cáo khoa học: "ADAPTING AN ENGLISH MORPHOLOGICAL ANALYZER FOR FRENCH"

A word-based morphological analyzer and a dictionary for recognizing inflected forms of French words have been built by adapting the UDICI" system. We describe the adaptations, emphasizing mechanisms developed to handle French verbs. This work lays the groundwork for doing French derivational morphology and morphology for other languages. | ADAPTING AN ENGLISH MORPHOLOGICAL ANALYZER FOR FRENCH Roy J. Byrd and Evelyne Tzoukcrmann IBM Research IBM Thomas J. Watson Research Center Yorktown Heights New York 10598 ABSTRACT A word-based morphological analyzer and a dictionary for recognizing inflected forms of French words have been built by adapting the UD1CT system. We describe the adaptations emphasizing mechanisms developed to handle French verbs. This work lays the groundwork for doing French derivational morphology and morphology for other languages. 1. Introduction. UDICT is a dictionary system intended to support the lexical needs of computer programs that do natural language processing NLP . Its first version was built for English and has been used in several systems needing a variety of information about English words Heidom et al. 1982 Sowa 1984 McCord 1986 and Neff and Byrd 1987 . As described in Byrd 1986 UDICT provides a framework for supplying syntactic semantic phonological and morphological information about the words it contains. Part of UDICT s apparatus is a morphological analysis subsystem capable of recognizing morphological variants of the words whose lemma forms are stored in UDICT s dictionary. The English version of this analyzer has been described in Byrd 1983 and Byrd et al. 1986 and allows ƯDICT to recognize inflectionally and derivationally affixed words compounds and collocations. The present paper describes an effort to build a French version of UD1CT. It briefly discusses the creation of the dictionary data itself and then focuses on issues raised in handling French inflectional morphology. 2. The Dictionary. The primary role of the dictionary in an NLP system is to store and retrieve information about words. In order for NLP systems to be effective their dictionaries must contain a lot of information about a lot of words. Chodorow et al. 1985 and Byrd et al. 1987 discuss techniques for building dictionaries with the required scope by extracting lexical information from .

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