A Practical Entity Linking System for Tables in Scientific Literature
Varish Mulwad Tim Finin Vijay S. Kumar Jenny Weisenberg Williams Sharad Dixit Anupam Joshi
Entity linking is an important step towards constructing knowledge graphs
that facilitate advanced question answering over scientific documents,
including the retrieval of relevant information included in tables within these
documents. This paper introduces a general-purpose system for linking entities
to items in the Wikidata knowledge base. It describes how we adapt this system
for linking domain-specific entities, especially for those entities embedded
within tables drawn from COVID-19-related scientific literature. We describe
the setup of an efficient offline instance of the system that enables our
entity-linking approach to be more feasible in practice. As part of a broader
approach to infer the semantic meaning of scientific tables, we leverage the
structural and semantic characteristics of the tables to improve overall entity
linking performance.