Abstract
This paper describes BomJi, a supervised system for capturing discriminative attributes in word pairs (e.g. yellow as discriminative for banana over watermelon). The system relies on an XGB classifier trained on carefully engineered graph-, pattern- and word embedding-based features. It participated in the SemEval-2018 Task 10 on Capturing Discriminative Attributes, achieving an F1 score of 0.73 and ranking 2nd out of 26 participant systems.- Anthology ID:
- S18-1163
- 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:
- 990–994
- Language:
- URL:
- https://aclanthology.org/S18-1163
- DOI:
- 10.18653/v1/S18-1163
- Cite (ACL):
- Enrico Santus, Chris Biemann, and Emmanuele Chersoni. 2018. BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 990–994, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes (Santus et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/S18-1163.pdf