It’s All in the Name: Entity Typing Using Multilingual Language Models

Russa Biswas, Yiyi Chen, Heiko Paulheim, Harald Sack, Mehwish Alam

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The entity type information in Knowledge Graphs (KGs) of different languages plays an important role in a wide range of Natural Language Processing applications. However, the entity types in KGs are often incomplete. Multilingual entity typing is a non-trivial task if enough information is not available for the entities in a KG. In this work, multilingual neural language models are exploited to predict the type of an entity from only the name of the entity. The model has been successfully evaluated on multilingual datasets extracted from different language chapters in DBpedia namely German, French, Spanish, and Dutch.

Original languageEnglish
Title of host publicationThe Semantic Web
Subtitle of host publicationESWC 2022 Satellite Events - Proceedings
EditorsPaul Groth, Anisa Rula, Jodi Schneider, Ilaria Tiddi, Elena Simperl, Panos Alexopoulos, Rinke Hoekstra, Mehwish Alam, Anastasia Dimou, Minna Tamper, Minna Tamper
PublisherSpringer Science and Business Media Deutschland GmbH
Pages36-41
Number of pages6
ISBN (Print)9783031116087
DOIs
Publication statusPublished - 1 Jan 2022
Externally publishedYes
Event19th European Semantic Web Conference, ESWC 2022 - Hersonissos, Greece
Duration: 29 May 20222 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13384 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th European Semantic Web Conference, ESWC 2022
Country/TerritoryGreece
CityHersonissos
Period29/05/222/06/22

Keywords

  • Classification
  • Entity type prediction
  • Knowledge graph completion
  • Multilingual language models

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