Abstract
We present SUNNYNLP, our system for solving SemEval 2018 Task 10: “Capturing Discriminative Attributes”. Our Support-Vector-Machine(SVM)-based system combines features extracted from pre-trained embeddings and statistical information from Is-A taxonomy to detect semantic difference of concepts pairs. Our system is demonstrated to be effective in detecting semantic difference and is ranked 1st in the competition in terms of F1 measure. The open source of our code is coined SUNNYNLP.- Anthology ID:
- S18-1118
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venues:
- SemEval | *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 741–746
- Language:
- URL:
- https://aclanthology.org/S18-1118
- DOI:
- 10.18653/v1/S18-1118
- Cite (ACL):
- Sunny Lai, Kwong Sak Leung, and Yee Leung. 2018. SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding Features. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 741–746, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding Features (Lai et al., SemEval-*SEM 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S18-1118.pdf
- Code
- Yermouth/sunnynlp
- Data
- YAGO