Paper: Fast Semantic Extraction Using a Novel Neural Network Architecture

ACL ID P07-1071
Title Fast Semantic Extraction Using a Novel Neural Network Architecture
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

We describe a novel neural network archi- tecture for the problem of semantic role la- beling. Many current solutions are compli- cated, consist of several stages and hand- built features, and are too slow to be applied as part of real applications that require such semantic labels, partly because of their use of a syntactic parser (Pradhan et al. , 2004; Gildea and Jurafsky, 2002). Our method in- stead learns a direct mapping from source sentence to semantic tags for a given pred- icate without the aid of a parser or a chun- ker. Our resulting system obtains accuracies comparable to the current state-of-the-art at a fraction of the computational cost.