K aushik A charya at S em E val-2021 Task 9: Candidate Generation for Fact Verification over Tables (2021)

Abstract: This paper describes the system submitted in the SemEval-2021 Statement Verification and Evidence Finding with Tables task. The system relies on candidate generation for logical forms on the table based on keyword matching and dependency parsing on the claim statements.

## introduction tables convey important information in a concise manner. this is true in many domains, scientific documents being one of them. truth verification tasks in past(e.g. semeval-2019 fact checking task) have focused on written text without considering the tables. the current shared task @xcite focuses on tables written in english language. it requires participants to develop systems to predict the shared task foot_0 comprised of two sub-tasks: ## results averaged f1 score over the tables are shown in ## conclusion i have described the system used for submission to the statement verification and evidence finding with tables task. the problem has been framed as a candidate generation for logical forms over dataframe using keyword matching and dependency parsing. future work would include extending the defined list of candidates and usage of scoring based system to identify the most probable candidate. this improvement would take ideas from @xcite for feature extraction and build a log-linear model to compute score for the candidates.