The use of syntactic structure in relationship extraction

This thesis describes a method of relationship extraction that uses surface and syntactic features of text along with entity detection information to perform sentence-level relationship extraction tasks. The tasks are to build and test classifiers for the following relationships: employer-employee, organization-location, family, and person-location. Methods of reducing noise in these features sets are also discussed, and experimental evidence of their effectiveness is presented. Performance of the system is analyzed in terms of precision and recall, and errors of the system are discussed along with proposed solutions. Finally a reformulation of the problem is presented along with a discussion of future work.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Singh-Miller, Natasha, 1981-

Advisor dc:contributor.advisor

• Michael J. Collins.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/17990

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/17990