Team UMBC-FEVER : Claim verification using Semantic Lexical Resources

By Ankur Padia, Francis Ferraro, Timothy W. Finin. 2018

6 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Information Systems, Natural Language Processing, Information Extraction

Citations in the corpus

• Reasoning Over Semantic-Level Graph for Fact Checking (2019, neutral): “Padia et al. (2018) utilizes semantic frames for evidence selection.”