Abstract
In this system description of our pipeline to participate at the Fever Shared Task, we describe our sentence-based approach. Throughout all steps of our pipeline, we regarded single sentences as our processing unit. In our IR-Component, we searched in the set of all possible Wikipedia introduction sentences without limiting sentences to a fixed number of relevant documents. In the entailment module, we judged every sentence separately and combined the result of the classifier for the top 5 sentences with the help of an ensemble classifier to make a judgment whether the truth of a statement can be derived from the given claim.- Anthology ID:
- W18-5524
- Volume:
- Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)
- Month:
- November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- James Thorne, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, Arpit Mittal
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 145–149
- Language:
- URL:
- https://aclanthology.org/W18-5524
- DOI:
- 10.18653/v1/W18-5524
- Cite (ACL):
- Wolfgang Otto. 2018. Team GESIS Cologne: An all in all sentence-based approach for FEVER. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 145–149, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Team GESIS Cologne: An all in all sentence-based approach for FEVER (Otto, EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-5524.pdf
- Data
- FEVER