@inproceedings{pais-etal-2021-named,
title = "Named Entity Recognition in the {R}omanian Legal Domain",
author = "Pais, Vasile and
Mitrofan, Maria and
Gasan, Carol Luca and
Coneschi, Vlad and
Ianov, Alexandru",
editor = "Aletras, Nikolaos and
Androutsopoulos, Ion and
Barrett, Leslie and
Goanta, Catalina and
Preotiuc-Pietro, Daniel",
booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2021",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.nllp-1.2",
doi = "10.18653/v1/2021.nllp-1.2",
pages = "9--18",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Named Entity Recognition in the Romanian Legal Domain
%A Pais, Vasile
%A Mitrofan, Maria
%A Gasan, Carol Luca
%A Coneschi, Vlad
%A Ianov, Alexandru
%Y Aletras, Nikolaos
%Y Androutsopoulos, Ion
%Y Barrett, Leslie
%Y Goanta, Catalina
%Y Preotiuc-Pietro, Daniel
%S Proceedings of the Natural Legal Language Processing Workshop 2021
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F pais-etal-2021-named
%X 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.
%R 10.18653/v1/2021.nllp-1.2
%U https://aclanthology.org/2021.nllp-1.2
%U https://doi.org/10.18653/v1/2021.nllp-1.2
%P 9-18
Markdown (Informal)
[Named Entity Recognition in the Romanian Legal Domain](https://aclanthology.org/2021.nllp-1.2) (Pais et al., NLLP 2021)
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.