@inproceedings{cabrera-diego-gheewala-2023-jus,
    title = "Jus Mundi at {S}em{E}val-2023 Task 6: Using a Frustratingly Easy Domain Adaption for a Legal Named Entity Recognition System",
    author = "Cabrera-Diego, Luis Adri{\'a}n  and
      Gheewala, Akshita",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2023.semeval-1.247/",
    doi = "10.18653/v1/2023.semeval-1.247",
    pages = "1783--1790",
    abstract = "In this work, we present a Named Entity Recognition (NER) system that was trained using a Frustratingly Easy Domain Adaptation (FEDA) over multiple legal corpora. The goal was to create a NER capable of detecting 14 types of legal named entities in Indian judgments. Besides the FEDA architecture, we explored a method based on overlapping context and averaging tensors to process long input texts, which can be beneficial when processing legal documents. The proposed NER reached an F1-score of 0.9007 in the sub-task B of Semeval-2023 Task 6, Understanding Legal Texts."
}