Paper: Semantic Role Labeling Via Consensus In Pattern-Matching

ACL ID W05-0626
Title Semantic Role Labeling Via Consensus In Pattern-Matching
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005
Authors

This paper describes a system for semantic role labeling for the CoNLL2005 Shared task. We divide the task into two sub-tasks: boundary recognition by a general tree- based predicate-argument recognition algo- rithm to convert a parse tree into a flat rep- resentation of all predicates and their related boundaries, and role labeling by a consensus model using a pattern-matching framework to find suitable roles for core constituents and adjuncts. We describe the system architecture and report results for the CoNLL2005 development dataset.