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

EasyChair Preprint 7809

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.

Keyphrases: Classification, Entity Type Prediction, Knowledge Graph Completion, Multilingual Language Models

@booklet{EasyChair:7809,
  author    = {Russa Biswas and Yiyi Chen and Heiko Paulheim and Harald Sack and Mehwish Alam},
  title     = {It's All in the Name: Entity Typing Using Multilingual Language Models},
  howpublished = {EasyChair Preprint 7809},
  year      = {EasyChair, 2022}}