Paper Info
Title
Exploiting Multiply Annotated Corpora in Biomedical Information Extraction Tasks
Abstract
This paper discusses the problem of utilising multiply annotated data in training biomedical information extraction systems. Two corpora, annotated with entities and relations, and containing a number of multiply annotated documents, are used to train named entity recognition and relation extraction systems. Several methods of automatically combining the multiple annotations to produce a single annotation are compared, but none produces better results than simply picking one of the annotated versions at random. It is also shown that adding extra singly annotated documents produces faster performance gains than adding extra multiply annotated documents.
Year
Venue
Keywords
2008
SIXTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, LREC 2008
relation extraction,information extraction
Field
DocType
Citations 
Annotation,Information retrieval,Computer science,Information extraction,Artificial intelligence,Natural language processing,Named-entity recognition,Relationship extraction
Conference
2
PageRank 
References 
Authors
0.35
9
2
Name
Order
Citations
PageRank
Barry Haddow1116367.08
Beatrice Alex223725.59