← Back to papers
2021 SEMEVAL SemEval 2021

KaushikAcharya at SemEval-2021 Task 9: Candidate Generation for Fact Verification over Tables

Abstract

AbstractThis 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.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Kaushik Acharya

Topics

Natural Language Processing > Applications > Fact-Checking Natural Language Processing > Applications > Information Extraction

Keywords

fact verification dependency parsing table processing candidate generation keyword matching
Download PDF

Related papers

UIT-ISE-NLP at SemEval-2021 Task 5: Toxic Spans Detection with BiLSTM-CRF and ToxicBERT Comment Classification 2021
BOUN at SemEval-2021 Task 9: Text Augmentation Techniques for Fact Verification in Tabular Data 2021
Cambridge at SemEval-2021 Task 2: Neural WiC-Model with Data Augmentation and Exploration of Representation 2021
CLULEX at SemEval-2021 Task 1: A Simple System Goes a Long Way 2021
katildakat at SemEval-2021 Task 1: Lexical Complexity Prediction of Single Words and Multi-Word Expressions in English 2021