COVID-19 Claim Radar: A Structured Claim Extraction and Tracking System

摘要

To tackle the challenge of accurate and timely communication regarding the COVID-19 pandemic, we present a COVID-19 Claim Radar to automatically extract supporting and refuting claims on a daily basis. We provide a comprehensive structured view of claims, including rich claim attributes (such as claimers and claimer affiliations) and associated knowledge elements as claim semantics (such as events, relations and entities), enabling users to explore equivalent, refuting, or supporting claims with structural evidence, such as shared claimers, similar centroid events and arguments. In order to consolidate claim structures at the corpus-level, we leverage Wikidata as the hub to merge coreferential knowledge elements. The system automatically provides users a comprehensive exposure to COVID-19 related claims, their importance, and their interconnections. The system is publicly available at GitHub and DockerHub, with complete documentation.

类型
出版物
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
于鹏飞
于鹏飞
在读计算机博士

我的科研方向为自然语言处理。我的科研经历主要在信息抽取和知识获取上。