USAAR-WLV: Hypernym Generation with Deep Neural Nets

This paper describes the USAAR-WLV taxonomy induction system that participated in the Taxonomy Extraction Evaluation task of SemEval-2015. We extend prior work on using vector space word embedding models for hypernym-hyponym extraction by simplifying the means to extract a projection matrix that transforms any hyponym to its hypernym. This is done by making use of function words, which are usually overlooked in vector space approaches to NLP. Our system performs best in the chemical domain and has achieved competitive results in the overall evaluations.

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USAAR-WLV: Hypernym Generation with Deep Neural Nets

Semantic Scholar · Chemistry · 2015

Abstract

This paper describes the USAAR-WLV taxonomy induction system that participated in the Taxonomy Extraction Evaluation task of SemEval-2015. We extend prior work on using vector space word embedding models for hypernym-hyponym extraction by simplifying the means to extract a projection matrix that transforms any hyponym to its hypernym. This is done by making use of function words, which are usually overlooked in vector space approaches to NLP. Our system performs best in the chemical domain and has achieved competitive results in the overall evaluations.

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