Proceedings of the Third Workshop on Scientific Document Understanding at AAAI-2023

A Practical Entity Linking System for Tables in Scientific Literature

, , , , , and

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.


  • 685747 bytes

  • 31405134 bytes

  • 3020180 bytes

covid, entity linking, knowledge graph, tables, wikidata

InProceedings

AAAI

Downloads: 797 downloads

UMBC ebiquity