Automatic Extraction of Entities and Relation from Legal Documents

Judith Jeyafreeda Andrew


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.
Anthology ID:
W18-2401
Volume:
Proceedings of the Seventh Named Entities Workshop
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Nancy Chen, Rafael E. Banchs, Xiangyu Duan, Min Zhang, Haizhou Li
Venue:
NEWS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–8
Language:
URL:
https://aclanthology.org/W18-2401
DOI:
10.18653/v1/W18-2401
Bibkey:
Cite (ACL):
Judith Jeyafreeda Andrew. 2018. Automatic Extraction of Entities and Relation from Legal Documents. In Proceedings of the Seventh Named Entities Workshop, pages 1–8, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Automatic Extraction of Entities and Relation from Legal Documents (Andrew, NEWS 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-2401.pdf