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  4. PNEL: Pointer Network Based End-To-End Entity Linking over Knowledge Graphs
 
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2020
Conference Paper
Title

PNEL: Pointer Network Based End-To-End Entity Linking over Knowledge Graphs

Abstract
Question Answering systems are generally modelled as a pipeline consisting of a sequence of steps. In such a pipeline, Entity Linking (EL) is often the first step. Several EL models first perform span detection and then entity disambiguation. In such models errors from the span detection phase cascade to later steps and result in a drop of overall accuracy. Moreover, lack of gold entity spans in training data is a limiting factor for span detector training. Hence the movement towards end-to-end EL models began where no separate span detection step is involved. In this work we present a novel approach to end-to-end EL by applying the popular Pointer Network model, which achieves competitive performance. We demonstrate this in our evaluation over three datasets on the Wikidata Knowledge Graph.
Author(s)
Banerjee, Debayan  
Language Technology Group, Universität Hamburg
Chaudhuri, Debanjan
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Dubey, Mohnish  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Lehmann, Jens  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Mainwork
The Semantic Web - ISWC 2020. 19th International Semantic Web Conference. Proceedings. Pt.I  
Conference
International Semantic Web Conference (ISWC) 2020  
DOI
10.1007/978-3-030-62419-4_2
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • Entity Linking

  • question answering

  • Knowledge Graphs

  • Wikidata

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