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Do Judge an Entity by Its Name! Entity Typing Using Language Models

Do Judge an Entity by Its Name! Entity Typing Using Language Models

Published: 2021 Juni
Herausgeber: Ruben Verborgh, Anastasia Dimou, Aidan Hogan, Claudia d'Amato, Ilaria Tiddi, Arne Bröring, Simon Maier, Femke Ongenae, Riccardo Tommasini, Mehwish Alam
Buchtitel: The Semantic Web: ESWC 2021 Satellite Events
Ausgabe: 12739
Seiten: 65-70
Verlag: Springer International Publishing
Erscheinungsort: Cham
Organisation: 18th European Semantic Web Conference, ESWC 2021

Referierte Veröffentlichung


The entity type information in a Knowledge Graph (KG) plays an important role in a wide range of applications in Natural Lan- guage Processing such as entity linking, question answering, relation ex- traction, etc. However, the available entity types are often noisy and incomplete. Entity Typing is a non-trivial task if enough information is not available for the entities in a KG. In this work, neural language models and a character embedding model are exploited to predict the type of an entity from only the name of the entity without any other information from the KG. The model has been successfully evaluated on a benchmark dataset.

Download: Media:2021-Biswas-Sofronova-Alam-Sack-P&D @ESWC2021-Do-Judge-an-Entity-by-its.pdf
Weitere Informationen unter: Link
DOI Link: 10.1007/978-3-030-80418-3_12


Information Service Engineering