Investigating the cross-lingual translatability of VerbNet-style classification.
VerbNet—the most extensive online verb lexicon currently available for English—has proved useful in supporting a variety of NLP tasks. However, its exploitation in multilingual NLP has been limited by the fact that such classifications are available for few languages only. Since manual development o...
| Publicado en: | Language Resources & Evaluation Vol. 52; no. 3; pp. 771 - 800 |
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| Autores principales: | , , , , , , |
| Formato: | Artículo |
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Springer Nature
Sep2018
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=131216684&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 131216684 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2018 vid: 52 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 131216684 10.1007/s10579-017-9403-x ppf: 771 ppct: 29 formats: fmt: – @attributes: type: T – @attributes: type: P size: 559KB tig: atl: Investigating the cross-lingual translatability of VerbNet-style classification. aug: au: Majewska, Olga Vulić, Ivan McCarthy, Diana Huang, Yan Murakami, Akira Korhonen, Anna Laippala, Veronika affil: Language Technology Lab (LTL), Department of Theoretical and Applied Linguistics (DTAL), University of Cambridge, 9 West Road, CB3 9DP, Cambridge, UK Department of French Studies, University of Turku, 20014, Turku, Finland su: Lexicon Multilingual computing Study & teaching of verbs General semantics Semantics sug: subj: Lexicon Multilingual computing Study & teaching of verbs General semantics Semantics keyword: Levin verb classes Lexical-semantic classification Multilingual NLP VerbNet ab: VerbNet—the most extensive online verb lexicon currently available for English—has proved useful in supporting a variety of NLP tasks. However, its exploitation in multilingual NLP has been limited by the fact that such classifications are available for few languages only. Since manual development of VerbNet is a major undertaking, researchers have recently translated VerbNet classes from English to other languages. However, no systematic investigation has been conducted into the applicability and accuracy of such a translation approach across different, typologically diverse languages. Our study is aimed at filling this gap. We develop a systematic method for translation of VerbNet classes from English to other languages which we first apply to Polish and subsequently to Croatian, Mandarin, Japanese, Italian, and Finnish. Our results on Polish demonstrate high translatability with all the classes (96% of English member verbs successfully translated into Polish) and strong inter-annotator agreement, revealing a promising degree of overlap in the resultant classifications. The results on other languages are equally promising. This demonstrates that VerbNet classes have strong cross-lingual potential and the proposed method could be applied to obtain gold standards for automatic verb classification in different languages. We make our annotation guidelines and the six language-specific verb classifications available with this paper. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2018. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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