A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling

Diego Marcheggiani; Anton Frolov; Ivan Titov

2017 CoNLL CoNLL 2017

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

📈 Trend Setter - Natural Language Processing

🐣 Hot Topic Early Bird - semantic role labeling

Authors

Diego Marcheggiani, Anton Frolov, Ivan Titov

Topics

Deep Learning > Architectures > Neural Networks Natural Language Processing Natural Language Processing > Understanding > Semantic Analysis Natural Language Processing > Understanding > Syntax Artificial Intelligence > Core AI > Reasoning Natural Language Processing > Applications > Semantic Parsing

Keywords

dependency parsing semantic role labeling bidirectional lstm predicate-argument structure syntax-agnostic model predicate-argument dependency

Download PDF