tailieunhanh - Báo cáo khoa học: "A System for Large-Scale Acquisition of Verbal, Nominal and Adjectival Subcategorization Frames from Corpora"

This paper describes the first system for large-scale acquisition of subcategorization frames (SCFs) from English corpus data which can be used to acquire comprehensive lexicons for verbs, nouns and adjectives. The system incorporates an extensive rulebased classifier which identifies 168 verbal, 37 adjectival and 31 nominal frames from grammatical relations (GRs) output by a robust parser. The system achieves state-ofthe-art performance on all three sets. | A System for Large-Scale Acquisition of Verbal Nominal and Adjectival Subcategorization Frames from Corpora Judita Preiss Ted Briscoe and Anna Korhonen Computer Laboratory University of Cambridge 15 JJ Thomson Avenue Cambridge CB3 0FD UK Abstract This paper describes the first system for large-scale acquisition of subcategorization frames SCFs from English corpus data which can be used to acquire comprehensive lexicons for verbs nouns and adjectives. The system incorporates an extensive rulebased classifier which identifies 168 verbal 37 adjectival and 31 nominal frames from grammatical relations GRs output by a robust parser. The system achieves state-of-the-art performance on all three sets. 1 Introduction Research into automatic acquisition of lexical information from large repositories of unannotated text such as the web corpora of published text etc. is starting to produce large scale lexical resources which include frequency and usage information tuned to genres and sublanguages. Such resources are critical for natural language processing NLP both for enhancing the performance of state-of-art statistical systems and for improving the portability of these systems between domains. One type of lexical information with particular importance for NLP is subcategorization. Access to an accurate and comprehensive subcategorization lexicon is vital for the development of successful parsing technology . Carroll et al. 1998 important for many NLP tasks . automatic verb classification Schulte im Walde and Brew 2002 and useful for any application which can benefit from information about predicate-argument structure . Information Extraction IE Surdeanu et al. 2003 . The first systems capable of automatically learning a small number of verbal subcategorization frames SCFs from unannotated English corpora emerged over a decade ago Brent 1991 Manning 1993 . Subsequent research has yielded systems for English .

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