ParaNames: A Massively Multilingual Entity Name Corpus

TL;DR

ParaNames is the largest multilingual entity name corpus with 118 million names across 400 languages, aiding multilingual NLP tasks like name translation, transliteration, and entity recognition.

Contribution

It introduces ParaNames, the largest parallel name resource with standardized data for 400 languages, enabling improved multilingual named entity processing.

Findings

Created the largest multilingual name corpus to date.

Demonstrated application in multilingual name translation.

Resource is publicly available under CC BY 4.0.

Abstract

We introduce ParaNames, a multilingual parallel name resource consisting of 118 million names spanning across 400 languages. Names are provided for 13.6 million entities which are mapped to standardized entity types (PER/LOC/ORG). Using Wikidata as a source, we create the largest resource of this type to-date. We describe our approach to filtering and standardizing the data to provide the best quality possible. ParaNames is useful for multilingual language processing, both in defining tasks for name translation/transliteration and as supplementary data for tasks such as named entity recognition and linking. We demonstrate an application of ParaNames by training a multilingual model for canonical name translation to and from English. Our resource is released under a Creative Commons license (CC BY 4.0) at https://github.com/bltlab/paranames.