Paper: A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies

ACL ID W08-2122
Title A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2008
Authors

We propose a solution to the challenge of the CoNLL 2008 shared task that uses a generative history-based latent variable model to predict the most likely derivation of a synchronous dependency parser for both syntactic and semantic dependencies. The submitted model yields 79.1% macro- average F1 performance, for the joint task, 86.9% syntactic dependencies LAS and 71.0% semantic dependencies F1. A larger model trained after the deadline achieves 80.5% macro-average F1, 87.6% syntac- tic dependencies LAS, and 73.1% seman- tic dependencies F1.