Do Judge an Entity by its Name! Entity Typing using Language ModelsDownload PDF

Published: 19 Apr 2021, Last Modified: 05 May 2023ESWC2021 P&DReaders: Everyone
Keywords: Entity Type Prediction · Knowledge Graph Completion · Deep Neural Networks.
TL;DR: Entity typing in KGs only from the labels exploiting the language models
Abstract: The entity type information in a Knowledge Graph (KG) plays an important role in a wide range of applications in Natural Language Processing such as entity linking, question answering, relation extraction, etc. However, entity types are often noisy and incomplete. Entity Typing is a non-trivial task when 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 an entity without any other information from the KG. The model has been evaluated on a benchmark dataset.
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