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

Tomáš Brychcín and Tomáš Hercig and 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.

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