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Team UMBC-FEVER : Claim verification using Semantic Lexical Resources

Authors :
Tim Finin
Ankur Padia
Francis Ferraro
Source :
Proceedings of the First Workshop on Fact Extraction and VERification (FEVER).
Publication Year :
2018
Publisher :
Association for Computational Linguistics, 2018.

Abstract

Proceedings of the First Workshop on Fact Extraction and Verification<br />We describe our system used in the 2018 FEVER shared task. The system employed a frame-based information retrieval approach to select Wikipedia sentences providing evidence and used a two-layer multilayer perceptron to classify a claim as correct or not. Our submission achieved a score of 0.3966 on the Evidence F1 metric with accuracy of 44.79%, and FEVER score of 0.2628 F1 points.

Details

Database :
OpenAIRE
Journal :
Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)
Accession number :
edsair.doi.dedup.....00b37b5b84679c664bdd677a5333aff7
Full Text :
https://doi.org/10.18653/v1/w18-5527