Paper: Jointly Modeling WSD and SRL with Markov Logic

ACL ID C10-1019
Title Jointly Modeling WSD and SRL with Markov Logic
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

Semantic role labeling (SRL) and word sense disambiguation (WSD) are two fun- damental tasks in natural language pro- cessing to find a sentence-level seman- tic representation. To date, they have mostly been modeled in isolation. How- ever, this approach neglects logical con- straints between them. We therefore ex- ploit some pipeline systems which verify the automatic all word sense disambigua- tion could help the semantic role label- ing and vice versa. We further propose a Markov logic model that jointly labels se- mantic roles and disambiguates all word senses. By evaluating our model on the OntoNotes 3.0 data, we show that this joint approach leads to a higher perfor- mance for word sense disambiguation and semantic role labeling than those pipeline approaches.