Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association

Shiva Taslimipoor, Omid Rohanian, Le An Ha, Gloria Corpas Pastor, Ruslan Mitkov


Abstract
This paper describes the system submitted to SemEval 2018 shared task 10 ‘Capturing Dicriminative Attributes’. We use a combination of knowledge-based and co-occurrence features to capture the semantic difference between two words in relation to an attribute. We define scores based on association measures, ngram counts, word similarity, and ConceptNet relations. The system is ranked 4th (joint) on the official leaderboard of the task.
Anthology ID:
S18-1160
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:
972–976
Language:
URL:
https://aclanthology.org/S18-1160
DOI:
10.18653/v1/S18-1160
Bibkey:
Cite (ACL):
Shiva Taslimipoor, Omid Rohanian, Le An Ha, Gloria Corpas Pastor, and Ruslan Mitkov. 2018. Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 972–976, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association (Taslimipoor et al., SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1160.pdf