Abstract
Determining whether a given claim is supported by evidence is a fundamental NLP problem that is best modeled as Textual Entailment. However, given a large collection of text, finding evidence that could support or refute a given claim is a challenge in itself, amplified by the fact that different evidence might be needed to support or refute a claim. Nevertheless, most prior work decouples evidence finding from determining the truth value of the claim given the evidence. We propose to consider these two aspects jointly. We develop TwoWingOS (two-wing optimization strategy), a system that, while identifying appropriate evidence for a claim, also determines whether or not the claim is supported by the evidence. Given the claim, TwoWingOS attempts to identify a subset of the evidence candidates; given the predicted evidence, it then attempts to determine the truth value of the corresponding claim entailment problem. We treat this problem as coupled optimization problems, training a joint model for it. TwoWingOS offers two advantages: (i) Unlike pipeline systems it facilitates flexible-size evidence set, and (ii) Joint training improves both the claim entailment and the evidence identification. Experiments on a benchmark dataset show state-of-the-art performance.- Anthology ID:
- D18-1010
- Volume:
- Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
- Month:
- October-November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 105–114
- Language:
- URL:
- https://aclanthology.org/D18-1010
- DOI:
- 10.18653/v1/D18-1010
- Cite (ACL):
- Wenpeng Yin and Dan Roth. 2018. TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 105–114, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification (Yin & Roth, EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/D18-1010.pdf
- Code
- yinwenpeng/FEVER
- Data
- FEVER