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.
REF showed the experimental results that this approach improved the performance of a parser for Link Grammar.
Analysis Of Link Grammar On Biomedical Dependency Corpus Targeted At Protein-Protein Interactions
International Joint Workshop On Natural Language Processing In Biomedicine And Its Applications NLPBA BioNLP
Computer Science