ParaNames 1.0: Creating an Entity Name Corpus for 400+ Languages using Wikidata

Fuente: arXiv
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Autores principales: Sälevä, Jonne, Lignos, Constantine
Formato: Preprint
Publicado: 2024
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author Sälevä, Jonne
Lignos, Constantine
author_facet Sälevä, Jonne
Lignos, Constantine
contents We introduce ParaNames, a massively multilingual parallel name resource consisting of 140 million names spanning over 400 languages. Names are provided for 16.8 million entities, and each entity is mapped from a complex type hierarchy to a standard type (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 the usefulness of ParaNames on two tasks. First, we perform canonical name translation between English and 17 other languages. Second, we use it as a gazetteer for multilingual named entity recognition, obtaining performance improvements on all 10 languages evaluated.
format Preprint
id arxiv_https___arxiv_org_abs_2405_09496
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ParaNames 1.0: Creating an Entity Name Corpus for 400+ Languages using Wikidata
Sälevä, Jonne
Lignos, Constantine
Computation and Language
Artificial Intelligence
We introduce ParaNames, a massively multilingual parallel name resource consisting of 140 million names spanning over 400 languages. Names are provided for 16.8 million entities, and each entity is mapped from a complex type hierarchy to a standard type (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 the usefulness of ParaNames on two tasks. First, we perform canonical name translation between English and 17 other languages. Second, we use it as a gazetteer for multilingual named entity recognition, obtaining performance improvements on all 10 languages evaluated.
title ParaNames 1.0: Creating an Entity Name Corpus for 400+ Languages using Wikidata
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2405.09496