Paper: A Joint Model for Parsing Syntactic and Semantic Dependencies

ACL ID W08-2124
Title A Joint Model for Parsing Syntactic and Semantic Dependencies
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2008
Authors

This paper describes a system that jointly parses syntactic and semantic dependen- cies, presented at the CoNLL-2008 shared task (Surdeanu et al., 2008). It combines online Peceptron learning (Collins, 2002) with a parsing model based on the Eisner algorithm (Eisner, 1996), extended so as to jointly assign syntactic and semantic la- bels. Overall results are 78.11 global F1, 85.84 LAS, 70.35 semanticF1. Official re- sults for the shared task (63.29 global F1; 71.95 LAS; 54.52 semantic F1) were sig- nificantly lower due to bugs present at sub- mission time.