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
  • [21] Automatic keyphrase extraction from chinese news documents
    Wang, HF
    Li, SJ
    Yu, SW
    FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, PT 2, PROCEEDINGS, 2005, 3614 : 648 - 657
  • [22] Automatic extraction of table metadata from digital documents
    Liu, Ying
    Mitra, Prasenjit
    Giles, C. Lee
    Bai, Kun
    OPENING INFORMATION HORIZONS, 2006, : 339 - +
  • [23] Simple Method for Ontology Automatic Extraction from Documents
    Ponte Novelli, Andreia Dal
    Parente de Oliveira, Jose Maria
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2012, 3 (12) : 44 - 51
  • [24] Automatic Extraction of Semantic Relations from Text Documents
    Ta, Chien D. C.
    Tuoi Phan Thi
    FUTURE DATA AND SECURITY ENGINEERING, FDSE 2016, 2016, 10018 : 344 - 351
  • [25] Automatic Catchphrase Identification from Legal Court Case Documents
    Mandal, Arpan
    Ghosh, Kripabandhu
    Pal, Arindam
    Ghosh, Saptarshi
    CIKM'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, 2017, : 2187 - 2190
  • [26] Corpus for Automatic Structuring of Legal Documents
    Kalamkar, Prathamesh
    Tiwari, Aman
    Agarwal, Astha
    Karn, Saurabh
    Gupta, Smita
    Raghavan, Vivek
    Modi, Ashutosh
    LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2022, : 4420 - 4429
  • [27] XML as a means to support information extraction from legal documents
    Martínez, MM
    de la Fuente, P
    Derniame, JC
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2003, 18 (05): : 263 - 277
  • [28] Automatic extraction of salient geometric entities from LIDAR point clouds
    Auer, Stefan
    Hinz, Stefan
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 2507 - 2510
  • [29] Automatic Extraction of Attributes and Entities for Product Differentiation
    Abhijeet Ramesh Thakare
    Parag S. Deshpande
    International Journal of Computational Intelligence Systems, 2018, 11 : 296 - 315
  • [30] Automatic Relation Extraction from Text: A Survey
    Li, Kun
    Zhang, Junsheng
    Yao, Changqing
    Shi, Chongde
    2016 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI), 2016, : 83 - 86