Automatic Extraction of Entities and Relation from Legal Documents

被引:0
|
作者
Andrew, Judith Jeyafreeda [1 ]
Tannier, Xavier [2 ]
机构
[1] Campus 2 UniCaen, GREYC, Batiment F,6 Blvd Marechal Juin, F-14000 Caen, France
[2] Sorbonne Univ, INSERM, LIMICS, Paris, France
来源
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1 / 8
页数:8
相关论文
共 50 条
  • [41] Event extraction and temporal reasoning in legal documents
    Schilder, Frank
    ANNOTATING, EXTRACTING AND REASONING ABOUT TIME AND EVENTS, 2007, 4795 : 59 - 71
  • [42] Unsupervised Keyword Extraction for Japanese Legal Documents
    Tho Thi Ngoc Le
    Minh Le Nguyen
    Shimazu, Akira
    LEGAL KNOWLEDGE AND INFORMATION SYSTEMS, 2013, 259 : 97 - 106
  • [43] An approach of information extraction from web documents for automatic ontology generation
    Yeom, KW
    Park, JH
    COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS, 2005, 3801 : 450 - 457
  • [44] Automatic extraction of data from 2-D plots in documents
    Lu, Xiaonan
    Wang, James Z.
    Mitra, Prasenjit
    Giles, C. Lee
    ICDAR 2007: NINTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS, 2007, : 188 - 192
  • [45] Automatic Information Extraction from Electronic Documents Using Machine Learning
    Kamaleson, Nishanthan
    Chu, Dominique
    Otero, Fernando E. B.
    ARTIFICIAL INTELLIGENCE XXXVIII, 2021, 13101 : 183 - 194
  • [46] Automatic extraction of domain-specific stopwords from labeled documents
    Makrehchi, Masoud
    Kamel, Mohamed S.
    ADVANCES IN INFORMATION RETRIEVAL, 2008, 4956 : 222 - 233
  • [47] Deep Text Mining for Automatic Keyphrase Extraction from Text Documents
    Abulaish, Muhammad
    Jahiruddin
    Dey, Lipika
    JOURNAL OF INTELLIGENT SYSTEMS, 2011, 20 (04) : 327 - 351
  • [48] Automatic Extraction of Access Control Policies from Natural Language Documents
    Narouei, Masoud
    Takabi, Hassan
    Nielsen, Rodney
    IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2020, 17 (03) : 506 - 517
  • [49] Automatic ontology-based knowledge extraction from web documents
    Alani, H
    Kim, S
    Millard, DE
    Weal, MJ
    Hall, W
    Lewis, PH
    Shadbolt, NR
    IEEE INTELLIGENT SYSTEMS, 2003, 18 (01) : 14 - 21
  • [50] Automatic extraction of titles from general documents using machine learning
    Hu, YH
    Li, H
    Cao, YB
    Meyerzon, D
    Zheng, QH
    PROCEEDINGS OF THE 5TH ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES, PROCEEDINGS, 2005, : 145 - 154