An information extraction customizer

Ralph Grishman; Yifan He

doi:10.1007/978-3-319-10816-2_1

An information extraction customizer

Ralph Grishman, Yifan He

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

When an information extraction system is applied to a new task or domain, we must specify the classes of entities and relations to be extracted. This is best done by a subject matter expert, who may have little training in NLP. To meet this need, we have developed a toolset which is able to analyze a corpus and aid the user in building the specifications of the entity and relation types.

Original language	English (US)
Title of host publication	Text, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings
Publisher	Springer Verlag
Pages	3-10
Number of pages	8
ISBN (Print)	9783319108155
DOIs	https://doi.org/10.1007/978-3-319-10816-2_1
State	Published - 2014
Event	17th International Conference on Text, Speech, and Dialogue, TSD 2014 - Brno, Czech Republic Duration: Sep 8 2014 → Sep 12 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8655 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	17th International Conference on Text, Speech, and Dialogue, TSD 2014
Country/Territory	Czech Republic
City	Brno
Period	9/8/14 → 9/12/14

Keywords

distributional analysis
information extraction

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-10816-2_1

Cite this

Grishman, R., & He, Y. (2014). An information extraction customizer. In Text, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings (pp. 3-10). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8655 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-10816-2_1

An information extraction customizer. / Grishman, Ralph; He, Yifan.
Text, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings. Springer Verlag, 2014. p. 3-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8655 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Grishman, R & He, Y 2014, An information extraction customizer. in Text, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8655 LNAI, Springer Verlag, pp. 3-10, 17th International Conference on Text, Speech, and Dialogue, TSD 2014, Brno, Czech Republic, 9/8/14. https://doi.org/10.1007/978-3-319-10816-2_1

@inproceedings{574f3c248fae4821b6d3545f5af6385d,

title = "An information extraction customizer",

abstract = "When an information extraction system is applied to a new task or domain, we must specify the classes of entities and relations to be extracted. This is best done by a subject matter expert, who may have little training in NLP. To meet this need, we have developed a toolset which is able to analyze a corpus and aid the user in building the specifications of the entity and relation types.",

keywords = "distributional analysis, information extraction",

author = "Ralph Grishman and Yifan He",

year = "2014",

doi = "10.1007/978-3-319-10816-2_1",

language = "English (US)",

isbn = "9783319108155",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "3--10",

booktitle = "Text, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings",

note = "17th International Conference on Text, Speech, and Dialogue, TSD 2014 ; Conference date: 08-09-2014 Through 12-09-2014",

}

TY - GEN

T1 - An information extraction customizer

AU - Grishman, Ralph

AU - He, Yifan

PY - 2014

Y1 - 2014

N2 - When an information extraction system is applied to a new task or domain, we must specify the classes of entities and relations to be extracted. This is best done by a subject matter expert, who may have little training in NLP. To meet this need, we have developed a toolset which is able to analyze a corpus and aid the user in building the specifications of the entity and relation types.

AB - When an information extraction system is applied to a new task or domain, we must specify the classes of entities and relations to be extracted. This is best done by a subject matter expert, who may have little training in NLP. To meet this need, we have developed a toolset which is able to analyze a corpus and aid the user in building the specifications of the entity and relation types.

KW - distributional analysis

KW - information extraction

UR - http://www.scopus.com/inward/record.url?scp=84906988930&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906988930&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-10816-2_1

DO - 10.1007/978-3-319-10816-2_1

M3 - Conference contribution

AN - SCOPUS:84906988930

SN - 9783319108155

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 3

EP - 10

BT - Text, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings

PB - Springer Verlag

T2 - 17th International Conference on Text, Speech, and Dialogue, TSD 2014

Y2 - 8 September 2014 through 12 September 2014

ER -

An information extraction customizer

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this