Begoña Villada Moirón

Also published as: Begoña Villada, Begoña Villada Moirón, M. Begoña Villada Moirón


2013

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Bitexts as Semantic Mirrors
Jörg Tiedemann | Lonneke van der Plas | Begoña Villada Moirón
Proceedings of the Workshop on Twenty Years of Bitext

2007

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Semantics-based Multiword Expression Extraction
Tim Van de Cruys | Begoña Villada Moirón
Proceedings of the Workshop on A Broader Perspective on Multiword Expressions

2006

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Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
Begoña Villada Moirón | Aline Villavicencio | Diana McCarthy | Stefan Evert | Suzanne Stevenson
Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties

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Identifying idiomatic expressions using automatic word-alignment
Begoña Villada Moirón | Jörg Tiedemann
Proceedings of the Workshop on Multi-word-expressions in a multilingual context

2005

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Linguistically enriched corpora for establishing variation in support verb constructions
Begoña Villada Moirón
Proceedings of the Sixth International Workshop on Linguistically Interpreted Corpora (LINC-2005)

2004

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A New Approach to the Corpus-based Statistical Investigation of Hungarian Multi-word Lexemes
Balázs Kis | Begoña Villada | Gosse Bouma | Gábor Ugray | Tamás Bíró | Gábor Pohl | John Nerbonne
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Discarding Noise in an Automatically Acquired Lexicon of Support verb Constructions
M. Begoña Villada Moirón
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

We applied data-driven methods to carry out automatic acquisition of Dutch prepositional support verb constructions (SVCs) in corpora (e.g., iets in de gaten houden (``keep an eye on something'')). This paper addresses the question whether linguistic diagnostics help to discard noise from the nbest lists and how to (semi-)automatically apply such linguistic diagnostics to parsed corpora. We show that some of the linguistic diagnostics proposed in Hollebrandse (1993) effectively identify SVCs and contribute a modest error rate decrease.