Constructing Biological Knowledge Bases by Extracting Information from Text Sources
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Extracting Biochemical Interactions from MEDLINE Using a Link Grammar Parser
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
A statistical parser for Czech
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Comparative experiments on learning information extractors for proteins and their interactions
Artificial Intelligence in Medicine
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Locality kernels for sequential data and their applications to parse ranking
Applied Intelligence
Molecular event extraction from link grammar parse trees
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Journal of Biomedical Informatics
LNLBioNLP '06 Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology
A robust linguistic platform for efficient and domain specific web content analysis
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Locality-convolution kernel and its application to dependency parse ranking
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Regularized least-squares for parse ranking
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Relation mining over a corpus of scientific literature
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
A framework for biological event extraction from text
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
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In this paper, we present an evaluation of the Link Grammar parser on a corpus consisting of sentences describing protein-protein interactions. We introduce the notion of an interaction subgraph, which is the subgraph of a dependency graph expressing a protein-protein interaction. We measure the performance of the parser for recovery of dependencies, fully correct linkages and interaction subgraphs. We analyze the causes of parser failure and report specific causes of error, and identify potential modifications to the grammar to address the identified issues. We also report and discuss the effect of an extension to the dictionary of the parser.