In this paper we describe the participation of the Joint Research Centre, EC, in task 14 - Semantic Taxonomy Enrichment at SemEval 2016. The algorithm which we propose transforms each candidate definition into a term vector, where each dimension represents a term and its value is calculated by TF.IDF. We attach the candidate term as a hyponym to the WordNet synset with the most similar definition. The results we obtained are encouraging, considering the simplicity of our approach. The obtained F measure is below the average, but above one of the baselines.
Deftor at SemEval-2016 task 14: Taxonomy enrichment using definition vectors
ROTONDI, AGATA
2016-01-01
Abstract
In this paper we describe the participation of the Joint Research Centre, EC, in task 14 - Semantic Taxonomy Enrichment at SemEval 2016. The algorithm which we propose transforms each candidate definition into a term vector, where each dimension represents a term and its value is calculated by TF.IDF. We attach the candidate term as a hyponym to the WordNet synset with the most similar definition. The results we obtained are encouraging, considering the simplicity of our approach. The obtained F measure is below the average, but above one of the baselines.
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