# XLEnt: Mining a Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment

arXiv: https://arxiv.org/abs/2104.08597 · HTML: https://mlsanity.com/paper/2104.08597/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 28 references that are in the map.
- First posted on arXiv 17 Apr 2021.

## Builds on (most cited first, 8 of 8)

- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond](https://mlsanity.com/paper/1812.10464/) (2018)
- [WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia](https://mlsanity.com/paper/1907.05791/) (2019)
- [CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB](https://mlsanity.com/paper/1911.04944/) (2019)
- [CCAligned: A Massive Collection of Cross-Lingual Web-Document Pairs](https://mlsanity.com/paper/1911.06154/) (2019)
- [Neural Cross-Lingual Named Entity Recognition with Minimal Resources](https://mlsanity.com/paper/1808.09861/) (2018)
- [Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projection](https://mlsanity.com/paper/1707.02483/) (2017)
- [False-Friend Detection and Entity Matching via Unsupervised Transliteration](https://mlsanity.com/paper/1611.06722/) (2016)

## Built on by (most cited first, 15 of 15)

- [Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora](https://mlsanity.com/paper/2402.07446/) (2024)
- [Krey`ol-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages](https://mlsanity.com/paper/2405.05376/) (2024)
- [Transferring Knowledge Distillation for Multilingual Social Event Detection](https://mlsanity.com/paper/2108.03084/) (2021)
- [Graphemic Normalization of the Perso-Arabic Script](https://mlsanity.com/paper/2210.12273/) (2022)
- [Recovering document annotations for sentence-level bitext](https://mlsanity.com/paper/2406.03869/) (2024)
- [Cross-lingual Human-Preference Alignment for Neural Machine Translation with Direct Quality Optimization](https://mlsanity.com/paper/2409.17673/) (2024)
- [Token-level Ensembling of Models with Different Vocabularies](https://mlsanity.com/paper/2502.21265/) (2025)
- [From SALAMANDRA to SALAMANDRATA: BSC Submission for WMT25 General Machine Translation Shared Task](https://mlsanity.com/paper/2508.12774/) (2025)
- [Low-resource Bilingual Dialect Lexicon Induction with Large Language Models](https://mlsanity.com/paper/2304.09957/) (2023)
- [Charles Translator: A Machine Translation System between Ukrainian and Czech](https://mlsanity.com/paper/2404.06964/) (2024)
- [Pula: Training Large Language Models for Setswana](https://mlsanity.com/paper/2408.02239/) (2024)
- [Language Varieties of Italy: Technology Challenges and Opportunities](https://mlsanity.com/paper/2209.09757/) (2022)
- [The African Languages Lab: A Collaborative Approach to Advancing Low-Resource African NLP](https://mlsanity.com/paper/2510.05644/) (2025)
- ["Chi nas dal soch el sent de legn" -- Auditing Text Corpora for Lombard](https://mlsanity.com/paper/2606.06349/) (2026)
- [Reference-Grounded Data Curation for Instruction-Following Thai-English Machine Translation](https://mlsanity.com/paper/2609.34770/) (2026)

## Abstract (arXiv)

Cross-lingual named-entity lexica are an important resource to multilingual NLP tasks such as machine translation and cross-lingual wikification. While knowledge bases contain a large number of entities in high-resource languages such as English and French, corresponding entities for lower-resource languages are often missing. To address this, we propose Lexical-Semantic-Phonetic Align (LSP-Align), a technique to automatically mine cross-lingual entity lexica from mined web data. We demonstrate LSP-Align outperforms baselines at extracting cross-lingual entity pairs and mine 164 million entity pairs from 120 different languages aligned with English. We release these cross-lingual entity pairs along with the massively multilingual tagged named entity corpus as a resource to the NLP community.