UMDuluth-CS8761 at SemEval-2018 Task 9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings

TL;DR

This paper presents methods for hypernym discovery using Hearst Patterns, co-occurrence frequencies, and word embeddings, achieving competitive results in SemEval-2018 Task 9.

Contribution

It introduces a hybrid approach combining pattern-based, frequency-based, and embedding-based techniques for hypernym discovery.

Findings

Placed 6th out of 19 in concept hypernym identification

Ranked 12th out of 18 in entity hypernym identification

Demonstrated effectiveness of combined methods in hypernym discovery

Abstract

Hypernym Discovery is the task of identifying potential hypernyms for a given term. A hypernym is a more generalized word that is super-ordinate to more specific words. This paper explores several approaches that rely on co-occurrence frequencies of word pairs, Hearst Patterns based on regular expressions, and word embeddings created from the UMBC corpus. Our system Babbage participated in Subtask 1A for English and placed 6th of 19 systems when identifying concept hypernyms, and 12th of 18 systems for entity hypernyms.