EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery

Ahmad Issa Alaa Aldine, Mounira Harzallah, Giuseppe Berio, Nicolas Béchet, Ahmad Faour

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Abstract
In this paper, we present our proposed system (EXPR) to participate in the hypernym discovery task of SemEval 2018. The task addresses the challenge of discovering hypernym relations from a text corpus. Our proposal is a combined approach of path-based technique and distributional technique. We use dependency parser on a corpus to extract candidate hypernyms and represent their dependency paths as a feature vector. The feature vector is concatenated with a feature vector obtained using Wikipedia pre-trained term embedding model. The concatenated feature vector fits a supervised machine learning method to learn a classifier model. This model is able to classify new candidate hypernyms as hypernym or not. Our system performs well to discover new hypernyms not defined in gold hypernyms.
Anthology ID:
S18-1150
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:
919–923
Language:
URL:
https://aclanthology.org/S18-1150
DOI:
10.18653/v1/S18-1150
Bibkey:
Cite (ACL):
Ahmad Issa Alaa Aldine, Mounira Harzallah, Giuseppe Berio, Nicolas Béchet, and Ahmad Faour. 2018. EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 919–923, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery (Issa Alaa Aldine et al., SemEval 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/S18-1150.pdf
Data
SemEval-2018 Task-9