conftrace_
← Back to papers
2017 CONLL CoNLL 2017

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

🌉 Interdisciplinary Bridge - Artificial Intelligence and Deep Learning and Natural Language Processing
📈 Trend Setter - Semantic Analysis
🧭 Keyword Pioneer - syntax-agnostic model
🐝 Cross-Pollinator - Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
🐣 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

Related papers

Neural Sequence-to-sequence Learning of Internal Word Structure 2017
An Automatic Approach for Document-level Topic Model Evaluation 2017
Robust Coreference Resolution and Entity Linking on Dialogues: Character Identification on TV Show Transcripts 2017
Knowledge Tracing in Sequential Learning of Inflected Vocabulary 2017
A Probabilistic Generative Grammar for Semantic Parsing 2017