Named Entity Discovery and Alignment in Parallel Data

Zuzana Nevěřilová

2025

Abstract

The paper describes two experiments with named entity discovery and alignment for English-Czech parallel data. In the previous work, we enriched the Parallel Global Voices corpus with named entity recognition (NER) for both languages and named entity linking (NEL) annotations for English. The alignment experiment employs sentence transformers and cosine similarity to identify NE translations from English to Czech and possibly other languages. The discovery experiment uses the same method to find possible translations between named entities in English and Czech n-grams. The described method achieves an F1 score of 0.94 in finding alignments between recognized entities. However, the same method can also discover unknown named entities with an F1 score of 0.70. The result indicates the method can be used to recognize named entities in parallel data in cases where no NER model is available with sufficient quality.

Paper Citation

in Harvard Style

Nevěřilová Z. (2025). Named Entity Discovery and Alignment in Parallel Data. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1215-1220. DOI: 10.5220/0013311300003890

in Bibtex Style

@conference{icaart25,
author={Zuzana Nevěřilová},
title={Named Entity Discovery and Alignment in Parallel Data},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1215-1220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013311300003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Named Entity Discovery and Alignment in Parallel Data
SN - 978-989-758-737-5
AU - Nevěřilová Z.
PY - 2025
SP - 1215
EP - 1220
DO - 10.5220/0013311300003890
PB - SciTePress