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Annotating tense, mood and voice for English, French and German
Univ Stuttgart, Inst Maschinelle Sprachverarbeitung, Stuttgart, Germany;Ludwig Maximilians Univ Munchen, Ctr Informat & Sprachverarbeitung, Munich, Germany.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. Univ Geneva, Dept Linguist, Geneva, Switzerland.
Ludwig Maximilians Univ Munchen, Ctr Informat & Sprachverarbeitung, Munich, Germany.
Ludwig Maximilians Univ Munchen, Ctr Informat & Sprachverarbeitung, Munich, Germany.
2017 (English)In: Proceedings Of The 55th Annual Meeting Of The Association For Computational Linguistics (ACL 2017): System Demonstrations / [ed] Bansal, M Ji, H, Association for Computational Linguistics, 2017, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

We present the first open-source tool for annotating morphosyntactic tense, mood and voice for English, French and German verbal complexes. The annotation is based on a set of language-specific rules, which are applied on dependency trees and leverage information about lemmas, morphological properties and POS-tags of the verbs. Our tool has an average accuracy of about 76%. The tense, mood and voice features are useful both as features in computational modeling and for corpus-linguistic research.

Place, publisher, year, edition, pages
Association for Computational Linguistics, 2017. p. 1-6
National Category
General Language Studies and Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-399795DOI: 10.18653/v1/P17-4001ISI: 000493994000001OAI: oai:DiVA.org:uu-399795DiVA, id: diva2:1379463
Conference
55th Annual Meeting of the Association-for-Computational-Linguistics (ACL), Vancouver, Canada, July 30-Aug 04, 2017
Funder
German Research Foundation (DFG)EU, European Research Council, 644402EU, European Research Council, 640550Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-17Bibliographically approved

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