UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions


Tomáš Brychcín and Tomáš Hercig Josef Steinberger and Michal Konkol
Proceedings of The 12th International Workshop on Semantic Evaluation (2018)

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Research topics:

Semantic Analysis

Abstract

We present our UWB system for the task of capturing discriminative attributes at SemEval-2018. Given two words and an attribute, the system decides, whether this attribute is discriminative between the words or not. Assuming Distributional Hypothesis, i.e., a word meaning is related to the distribution across contexts, we introduce several approaches to compare word contextual information. We experiment with state-of-the-art semantic spaces and with simple co-occurrence statistics. We show the word distribution in the corpus has potential for detecting discriminative attributes. Our system achieves F1 score 72.1% and is ranked #4 among 26 submitted systems.

Authors

BibTex

@InProceedings{S18-1153, author = "Brychc{\'i}n, Tom{\'a}{\v{s}} and Hercig, Tom{\'a}{\v{s}} and Steinberger, Josef and Konkol, Michal", title = "UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions ", booktitle = "Proceedings of The 12th International Workshop on Semantic Evaluation", year = "2018", publisher = "Association for Computational Linguistics", pages = "935--939", location = "New Orleans, Louisiana", doi = "10.18653/v1/S18-1153", url = "http://aclweb.org/anthology/S18-1153" }
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