Vijay Kumar - Academia.edu (original) (raw)
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University of Maryland Baltimore County
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Papers by Vijay Kumar
Third Workshop on Scientific Document Understanding at AAAI-2023, 2023
Entity linking is an important step towards constructing knowledge graphs that facilitate advance... more Entity linking is an important step towards constructing knowledge graphs that facilitate advanced question answering over scientific documents-including the retrieval of relevant information present 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.
Third Workshop on Scientific Document Understanding at AAAI-2023, 2023
Entity linking is an important step towards constructing knowledge graphs that facilitate advance... more Entity linking is an important step towards constructing knowledge graphs that facilitate advanced question answering over scientific documents-including the retrieval of relevant information present 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.