UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings

Arshia Zernab Hassan, Manikya Swathi Vallabhajosyula, Ted Pedersen


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.
Anthology ID:
S18-1149
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
914–918
Language:
URL:
https://aclanthology.org/S18-1149
DOI:
10.18653/v1/S18-1149
Bibkey:
Cite (ACL):
Arshia Zernab Hassan, Manikya Swathi Vallabhajosyula, and Ted Pedersen. 2018. UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 914–918, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings (Hassan et al., SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1149.pdf
Data
SemEval-2018 Task-9