Abstract
The paper presents NTNU’s contribution to SemEval-2018 Task 7 on relation identification and classification. The class weights and parameters of five alternative supervised classifiers were optimized through grid search and cross-validation. The outputs of the classifiers were combined through voting for the final prediction. A wide variety of features were explored, with the most informative identified by feature selection. The best setting achieved F1 scores of 47.4% and 66.0% in the relation classification subtasks 1.1 and 1.2. For relation identification and classification in subtask 2, it achieved F1 scores of 33.9% and 17.0%,- Anthology ID:
- S18-1138
- 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:
- 858–862
- Language:
- URL:
- https://aclanthology.org/S18-1138
- DOI:
- 10.18653/v1/S18-1138
- Cite (ACL):
- Biswanath Barik, Utpal Kumar Sikdar, and Björn Gambäck. 2018. NTNU at SemEval-2018 Task 7: Classifier Ensembling for Semantic Relation Identification and Classification in Scientific Papers. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 858–862, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- NTNU at SemEval-2018 Task 7: Classifier Ensembling for Semantic Relation Identification and Classification in Scientific Papers (Barik et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/naacl24-info/S18-1138.pdf