This paper describes the NUIG-UNLP system submitted to SemEval-2016, Task 13. We implement a semi-supervised method that extracts hypernym candidates for the terms provided in the test list. The main assumption of our system is that hypernyms may be induced by adding a vector offset to the corresponding hyponym word embedding. The vector offset is obtained as the average offset between 200 pairs of hyponym-hypernym in the same vector space. Our approach ranked second on connectivity (c.c.) and categorisation (i.i.) for the English taxonomy construction, and fifth on the overall ranking. Despite of these modest results, our system achieved comparable evaluations scores with the other participants.
The only submission to the TExEval 2016 task that relied exclusively on distributional semantics to induce hypernyms by adding a vector offset to the corresponding hyponym REF achieved only modest results.
NUIG-UNLP at SemEval-2016 Task 13: A Simple Word Embedding-based Approach for Taxonomy Extraction
SemEval@NAACL-HLT
Computer Science