Bf3R at SemEval-2018 Task 7: Evaluating Two Relation Extraction Tools for Finding Semantic Relations in Biomedical Abstracts
Mariana Neves, Daniel Butzke, Gilbert Schönfelder, Barbara Grune
Abstract
Automatic extraction of semantic relations from text can support finding relevant information from scientific publications. We describe our participation in Task 7 of SemEval-2018 for which we experimented with two relations extraction tools - jSRE and TEES - for the extraction and classification of six relation types. The results we obtained with TEES were significantly superior than those with jSRE (33.4% vs. 30.09% and 20.3% vs. 16%). Additionally, we utilized the model trained with TEES for extracting semantic relations from biomedical abstracts, for which we present a preliminary evaluation.- Anthology ID:
- S18-1130
- 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:
- 816–820
- Language:
- URL:
- https://aclanthology.org/S18-1130
- DOI:
- 10.18653/v1/S18-1130
- Cite (ACL):
- Mariana Neves, Daniel Butzke, Gilbert Schönfelder, and Barbara Grune. 2018. Bf3R at SemEval-2018 Task 7: Evaluating Two Relation Extraction Tools for Finding Semantic Relations in Biomedical Abstracts. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 816–820, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Bf3R at SemEval-2018 Task 7: Evaluating Two Relation Extraction Tools for Finding Semantic Relations in Biomedical Abstracts (Neves et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/S18-1130.pdf