2005 SimpleAlgsForCompleRelExtrWithAppsToBioIE

• (McDonald et al., 2005b) ⇒ Ryan T. McDonald, Fernando Pereira, Seth Kulick, Scott Winters, Yang Jin, Pete White. (2005). “Simple Algorithms for Complex Relation Extraction with Applications to Biomedical IE.” In: Proceedings of the ACL Conference (ACL 2005).

Subject Headings: Complex Relation Mention Recognition Algorithm, Biomedical Information Extraction

Cited By

2008

• (Zhang, 2008)
  • QUOTE: While typical work in this area almost focuses on binary relations, McDonald et al. [7] presented a simple two-stage method for extracting complex (n-ary) relations between named entities in text. The first stage creates a graph from pairs of entities that are likely to be related, and the second stage scores maximal cliques in that graph as potential complex relation instances. The method is evaluated in the biomedical domain.

Quotes

Abstract

A complex relation is any n-ary relation in which some of the arguments may be unspecified. We present here a simple two-stage method for extracting complex relations between named entities in text. The first stage creates a graph from pairs of entities that are likely to be related, and the second stage scores maximal cliques in that graph as potential complex relation instances. We evaluate the new method against a standard baseline for extracting genomic variation relations from biomedical text.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2005 SimpleAlgsForCompleRelExtrWithAppsToBioIE	Ryan T. McDonald Fernando Pereira Yang Jin Seth Kulick Scott Winters Pete White			Simple Algorithms for Complex Relation Extraction with Applications to Biomedical IE		Proceedings of the ACL Conference	http://delivery.acm.org/10.1145/1220000/1219901/p491-mcdonald.pdf?key1=1219901&key2=0929047921&coll=DL&dl=ACM&CFID=8535024&CFTOKEN=73487060			2005