Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa

Martin Funkquist


Abstract
This paper describes a method for retrieving evidence and predicting the veracity of factual claims, on the FEVEROUS dataset. The evidence consists of both sentences and table cells. The proposed method is part of the FEVER shared task. It uses similarity scores between TF-IDF vectors to retrieve the textual evidence and similarity scores between dense vectors created by fine-tuned TaPaS models for tabular evidence retrieval. The evidence is passed through a dense neural network to produce a veracity label. The FEVEROUS score for the proposed system is 0.126.
Anthology ID:
2021.fever-1.10
Volume:
Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER)
Month:
November
Year:
2021
Address:
Dominican Republic
Venues:
EMNLP | FEVER
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
92–100
Language:
URL:
https://aclanthology.org/2021.fever-1.10
DOI:
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.fever-1.10.pdf
Data
FEVEROUS