This article is part of the supplement: Second International Symposium on Semantic Mining in Biomedicine (SMBM)
A critical review of PASBio's argument structures for biomedical verbs
1 Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO, USA
2 Dept of Linguistics, University of Colorado at Boulder, Colorado, USA
BMC Bioinformatics 2006, 7(Suppl 3):S5 doi:10.1186/1471-2105-7-S3-S5Published: 24 November 2006
Propositional representations of biomedical knowledge are a critical component of most aspects of semantic mining in biomedicine. However, the proper set of propositions has yet to be determined. Recently, the PASBio project proposed a set of propositions and argument structures for biomedical verbs. This initial set of representations presents an opportunity for evaluating the suitability of predicate-argument structures as a scheme for representing verbal semantics in the biomedical domain. Here, we quantitatively evaluate several dimensions of the initial PASBio propositional structure repository.
We propose a number of metrics and heuristics related to arity, role labelling, argument realization, and corpus coverage for evaluating large-scale predicate-argument structure proposals. We evaluate the metrics and heuristics by applying them to PASBio 1.0.
PASBio demonstrates the suitability of predicate-argument structures for representing aspects of the semantics of biomedical verbs. Metrics related to theta-criterion violations and to the distribution of arguments are able to detect flaws in semantic representations, given a set of predicate-argument structures and a relatively small corpus annotated with them.