@inproceedings{bott-schulte-im-walde-2017-factoring,
title = "Factoring Ambiguity out of the Prediction of Compositionality for {G}erman Multi-Word Expressions",
author = "Bott, Stefan and
Schulte im Walde, Sabine",
editor = "Markantonatou, Stella and
Ramisch, Carlos and
Savary, Agata and
Vincze, Veronika",
booktitle = "Proceedings of the 13th Workshop on Multiword Expressions ({MWE} 2017)",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-1708",
doi = "10.18653/v1/W17-1708",
pages = "66--72",
abstract = {Ambiguity represents an obstacle for distributional semantic models(DSMs), which typically subsume the contexts of all word senses within one vector. While individual vector space approaches have been concerned with sense discrimination (e.g., Sch{\"u}tze 1998, Erk 2009, Erk and Pado 2010), such discrimination has rarely been integrated into DSMs across semantic tasks. This paper presents a soft-clustering approach to sense discrimination that filters sense-irrelevant features when predicting the degrees of compositionality for German noun-noun compounds and German particle verbs.},
}
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<abstract>Ambiguity represents an obstacle for distributional semantic models(DSMs), which typically subsume the contexts of all word senses within one vector. While individual vector space approaches have been concerned with sense discrimination (e.g., Schütze 1998, Erk 2009, Erk and Pado 2010), such discrimination has rarely been integrated into DSMs across semantic tasks. This paper presents a soft-clustering approach to sense discrimination that filters sense-irrelevant features when predicting the degrees of compositionality for German noun-noun compounds and German particle verbs.</abstract>
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%0 Conference Proceedings
%T Factoring Ambiguity out of the Prediction of Compositionality for German Multi-Word Expressions
%A Bott, Stefan
%A Schulte im Walde, Sabine
%Y Markantonatou, Stella
%Y Ramisch, Carlos
%Y Savary, Agata
%Y Vincze, Veronika
%S Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F bott-schulte-im-walde-2017-factoring
%X Ambiguity represents an obstacle for distributional semantic models(DSMs), which typically subsume the contexts of all word senses within one vector. While individual vector space approaches have been concerned with sense discrimination (e.g., Schütze 1998, Erk 2009, Erk and Pado 2010), such discrimination has rarely been integrated into DSMs across semantic tasks. This paper presents a soft-clustering approach to sense discrimination that filters sense-irrelevant features when predicting the degrees of compositionality for German noun-noun compounds and German particle verbs.
%R 10.18653/v1/W17-1708
%U https://aclanthology.org/W17-1708
%U https://doi.org/10.18653/v1/W17-1708
%P 66-72
Markdown (Informal)
[Factoring Ambiguity out of the Prediction of Compositionality for German Multi-Word Expressions](https://aclanthology.org/W17-1708) (Bott & Schulte im Walde, MWE 2017)
ACL