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

arXiv: https://arxiv.org/abs/2405.09496 · HTML: https://mlsanity.com/paper/2405.09496/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 22 references that are in the map.
- First posted on arXiv 15 May 2024.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://mlsanity.com/paper/1904.01038/) (2019)
- [End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF](https://mlsanity.com/paper/1603.01354/) (2016)
- [MasakhaNER: Named Entity Recognition for African Languages](https://mlsanity.com/paper/2103.11811/) (2021)
- [Soft Gazetteers for Low-Resource Named Entity Recognition](https://mlsanity.com/paper/2005.01866/) (2020)
- [HiNER: A Large Hindi Named Entity Recognition Dataset](https://mlsanity.com/paper/2204.13743/) (2022)
- [Design Challenges in Named Entity Transliteration](https://mlsanity.com/paper/1808.02563/) (2018)
- [JRC-Names: A freely available, highly multilingual named entity resource](https://mlsanity.com/paper/1309.6162/) (2013)
- [Statistical and Neural Methods for Cross-lingual Entity Label Mapping in Knowledge Graphs](https://mlsanity.com/paper/2206.08709/) (2022)

## Built on by (most cited first, 5 of 5)

- [Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP](https://mlsanity.com/paper/2405.17159/) (2024)
- [ParsTranslit: Truly Versatile Tajik-Farsi Transliteration](https://mlsanity.com/paper/2510.07520/) (2025)
- [Efficient Multilingual Name Type Classification Using Convolutional Networks](https://mlsanity.com/paper/2601.11090/) (2026)
- [No PUN Intended: Plausible Unknown Names for Person-Centred LLM Evaluation](https://mlsanity.com/paper/2608.21206/) (2026)
- [When Names Cross Scripts: A Source-Grounded Benchmark for Historical Entity Reconciliation in the Mongol World](https://mlsanity.com/paper/2608.23507/) (2026)

## Abstract (arXiv)

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.