Named Entity Recognition in the Romanian Legal Domain

Vasile Pais, Maria Mitrofan, Carol Luca Gasan, Vlad Coneschi, Alexandru Ianov


Abstract
Recognition of named entities present in text is an important step towards information extraction and natural language understanding. This work presents a named entity recognition system for the Romanian legal domain. The system makes use of the gold annotated LegalNERo corpus. Furthermore, the system combines multiple distributional representations of words, including word embeddings trained on a large legal domain corpus. All the resources, including the corpus, model and word embeddings are open sourced. Finally, the best system is available for direct usage in the RELATE platform.
Anthology ID:
2021.nllp-1.2
Volume:
Proceedings of the Natural Legal Language Processing Workshop 2021
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Venues:
EMNLP | NLLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
9–18
Language:
URL:
https://aclanthology.org/2021.nllp-1.2
DOI:
10.18653/v1/2021.nllp-1.2
Bibkey:
Cite (ACL):
Vasile Pais, Maria Mitrofan, Carol Luca Gasan, Vlad Coneschi, and Alexandru Ianov. 2021. Named Entity Recognition in the Romanian Legal Domain. In Proceedings of the Natural Legal Language Processing Workshop 2021, pages 9–18, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Named Entity Recognition in the Romanian Legal Domain (Pais et al., NLLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.nllp-1.2.pdf
Code
 racai-ai/LegalNER
Data
LegalNERo