@inproceedings{sanchez-2019-sentence,
    title = "Sentence Boundary Detection in Legal Text",
    author = "Sanchez, George",
    editor = "Aletras, Nikolaos  and
      Ash, Elliott  and
      Barrett, Leslie  and
      Chen, Daniel  and
      Meyers, Adam  and
      Preotiuc-Pietro, Daniel  and
      Rosenberg, David  and
      Stent, Amanda",
    booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2019",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/W19-2204/",
    doi = "10.18653/v1/W19-2204",
    pages = "31--38",
    abstract = "In this paper, we examined several algorithms to detect sentence boundaries in legal text. Legal text presents challenges for sentence tokenizers because of the variety of punctuations and syntax of legal text. Out-of-the-box algorithms perform poorly on legal text affecting further analysis of the text. A novel and domain-specific approach is needed to detect sentence boundaries to further analyze legal text. We present the results of our investigation in this paper."
}