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Semi-automatic Verb Valence Frame Assignment through VerbNet Classification / Mikelić Preradović, Nives ; Boras, Damir.

By: Mikelić Preradović, Nives.
Contributor(s): Boras, Damir [aut].
Material type: ArticleArticleDescription: 492-500 str.ISBN: 9783-642-40584-6.Other title: Semi-automatic Verb Valence Frame Assignment through VerbNet Classification [Naslov na engleskom:].Subject(s): 5.04 | VerbNet classification, verb subcategorization, frame assignement, Croatian language, Czech language. hrv | VerbNet classification, verb subcategorization, frame assignement, Croatian language, Czech language. engOnline resources: Click here to access online In: Text, Speech, and Dialogue : 16th International Conference, TSD 2013, Pilsen, Czech Republic, September 1-5, 2013. : Proceedings International Conference, TSD 2013 (16 ; 2013 ; Pilsen, Czech Republic) str. 492-500Habernal, Ivan ; Matoušek, VáclavSummary: An approach to cross-linguistic transfer of verb valence frames for Czech and Croatian language using VerbNet syntactic-semantic classification is presented. Confronting Czech-Croatian pairs of valence frames for each syntacticsemantic class, we extracted the semantic part of the Czech valence frames and applied the subcategorization features to Croatian with minor (mainly syntactic) modifications. The encouraging results suggest that other similar (Slavic) languages could benefit from the same approach. It is shown that even for languages that do not have sufficiently developed NLP resources that are highly relevant for verb subcategorization (such asWordNet), it is possible to obtain valence lexicon applying small number of rules for cross-linguistic syntactic transfer and using Levin’s verb classes.
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An approach to cross-linguistic transfer of verb valence frames for Czech and Croatian language using VerbNet syntactic-semantic classification is presented. Confronting Czech-Croatian pairs of valence frames for each syntacticsemantic class, we extracted the semantic part of the Czech valence frames and applied the subcategorization features to Croatian with minor (mainly syntactic) modifications. The encouraging results suggest that other similar (Slavic) languages could benefit from the same approach. It is shown that even for languages that do not have sufficiently developed NLP resources that are highly relevant for verb subcategorization (such asWordNet), it is possible to obtain valence lexicon applying small number of rules for cross-linguistic syntactic transfer and using Levin’s verb classes.

Projekt MZOS 130-1301679-1380

ENG

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