Output details
11 - Computer Science and Informatics
University of Edinburgh
Article title
Datasets for generic relation extraction
Type
D - Journal article
Title of journal
Natural Language Engineering
Article number
-
Volume number
18
Issue number
1
First page of article
21
ISSN of journal
1469-8110
Year of publication
2012
Number of additional authors
2
Additional information
<22> Originality: This paper rationalises some of the concepts in the task of relation extraction (a sub-task of information extraction). A publicly available corpus (the ACE corpus) is converted into a form for training and testing of relation extraction systems. Its utility is demonstrated through a series of experiments that compare approaches to generic relation extraction.
Significance: Clarifies many issues in relation extraction and provides a revised ACE dataset to other researchers (distributed by the Linguistic Data Consortium, the main data provider to NLP researchers across the world).
Rigour: Formal evaluation of a relation extraction system on the new dataset.
Interdisciplinary
-
Cross-referral requested
-
Research group
D - Institute for Language, Cognition & Computation
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
