Van de Cruys, Tim
A neural network approach to selectional preference acquisition.
(2014)
In: Empirical Methods in Natural Language Processing (EMNLP), 25 October 2014 - 29 October 2014 (Doha, Qatar).
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(Document in English)
PDF (Publisher's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 199kB |
Official URL: https://doi.org/10.3115/v1/D14-1004
Abstract
This paper investigates the use of neural networks for the acquisition of selectional preferences. Inspired by recent advances of neural network models for NLP applications, we propose a neural network modelthat learns to discriminate between felicitous and infelicitous arguments for a particular predicate. The model is entirely unsupervised preferences are learned fromunannotated corpus data. We propose twoneural network architectures: one that handles standard two-way selectional prefer-ences and one that is able to deal with multi-way selectional preferences. Themodel’s performance is evaluated on a pseudo-disambiguation task, on which it is shown to achieve state of the art performance.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Thanks to Association for Computational Linguistics. Thi is an open accees article available at the URL: https://www.aclweb.org/anthology/D14-1004 |
HAL Id: | hal-02878928 |
Audience (conference): | International conference proceedings |
Uncontrolled Keywords: | |
Institution: | Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE) Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE) |
Laboratory name: | |
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Deposited On: | 16 Jun 2020 09:01 |
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