@inproceedings{andrew-2018-automatic,
    title = "Automatic Extraction of Entities and Relation from Legal Documents",
    author = "Andrew, Judith Jeyafreeda",
    editor = "Chen, Nancy  and
      Banchs, Rafael E.  and
      Duan, Xiangyu  and
      Zhang, Min  and
      Li, Haizhou",
    booktitle = "Proceedings of the Seventh Named Entities Workshop",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/W18-2401/",
    doi = "10.18653/v1/W18-2401",
    pages = "1--8",
    abstract = "In recent years, the journalists and computer sciences speak to each other to identify useful technologies which would help them in extracting useful information. This is called ``computational Journalism''. In this paper, we present a method that will enable the journalists to automatically identifies and annotates entities such as names of people, organizations, role and functions of people in legal documents; the relationship between these entities are also explored. The system uses a combination of both statistical and rule based technique. The statistical method used is Conditional Random Fields and for the rule based technique, document and language specific regular expressions are used."
}