LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

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Title Tuning Lexicons to New Operational Scenarios

Authors Basili Roberto (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), basili@info.uniroma2.it)
Pazienza Maria Teresa (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), pazienza@info.uniroma2.it)
Vindigni Michele (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), vindigni@info.uniroma2.it)
Zanzotto Fabio Massimo (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), zanzotto@info.uniroma2.it)

Keywords Event Recognition, Induction, Lexical Acquisition, Lexical Tuning, Lexicon, Word Sense Disambiguation

Session Session WO6 - Acquisition of Lexical Information

Abstract In this paper the role of the lexicon within typical application tasks based on NLP is analysed. A large scale semantic lexicon is studied within the framework of a NLP application. The coverage of the lexicon with respect the target domain and a (semi)automatic tuning approach have been evaluated. The impact of a corpus-driven inductive architecture aiming to compensate lacks in lexical information are thus measured and discussed.

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Title	Tuning Lexicons to New Operational Scenarios
Authors	Basili Roberto (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), basili@info.uniroma2.it) Pazienza Maria Teresa (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), pazienza@info.uniroma2.it) Vindigni Michele (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), vindigni@info.uniroma2.it) Zanzotto Fabio Massimo (University of Rome Tor Vergata, Department of Computer Science, Systems and Production, Via di Tor Vergata 110, 00133 Roma (Italy), zanzotto@info.uniroma2.it)
Keywords	Event Recognition, Induction, Lexical Acquisition, Lexical Tuning, Lexicon, Word Sense Disambiguation
Session	Session WO6 - Acquisition of Lexical Information
Abstract	In this paper the role of the lexicon within typical application tasks based on NLP is analysed. A large scale semantic lexicon is studied within the framework of a NLP application. The coverage of the lexicon with respect the target domain and a (semi)automatic tuning approach have been evaluated. The impact of a corpus-driven inductive architecture aiming to compensate lacks in lexical information are thus measured and discussed.