ParaNames: A Massively Multilingual Entity Name Corpus
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 5 of its 14 references that are in the map. First posted on arXiv 28 Feb 2022.
Builds on
5 of 14 references.
References · 5
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,486
- 2020Applying the Transformer to Character-level Transductioncited by 43
- 2018Design Challenges in Named Entity Transliterationcited by 11
- 2013JRC-Names: A freely available, highly multilingual named entity resourcecited by 6
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.