Use of deep linguistic features for the recognition and labeling of semantic arguments

Authors:
John Chen;Owen Rambow
Affiliations:
Columbia University, New York, NY;Columbia University, New York, NY
Venue:
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Year:
2003

Citing 9
Cited 26

Head-driven statistical models for natural language parsing

Head-driven statistical models for natural language parsing
Towards efficient statistical parsing using lexicalized grammatical information

Towards efficient statistical parsing using lexicalized grammatical information
Building a large annotated corpus of English: the penn treebank

Computational Linguistics - Special issue on using large corpora: II
Supertagging: an approach to almost parsing

Computational Linguistics
Statistical decision-tree models for parsing

ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
The necessity of parsing for predicate argument recognition

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical parsing with an automatically-extracted tree adjoining grammar

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The Penn Treebank: annotating predicate argument structure

HLT '94 Proceedings of the workshop on Human Language Technology
The SuperARV language model: investigating the effectiveness of tightly integrating multiple knowledge sources

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10

Semantic Role Parsing: Adding Semantic Structure to Unstructured Text

ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Support Vector Learning for Semantic Argument Classification

Machine Learning
The Proposition Bank: An Annotated Corpus of Semantic Roles

Computational Linguistics
Automated extraction of Tree-Adjoining Grammars from treebanks

Natural Language Engineering
Semantic role labeling using different syntactic views

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semantic role labeling using dependency trees

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Semantic role labeling via integer linear programming inference

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Deep linguistic analysis for the accurate identification of predicate-argument relations

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Tree kernels for semantic role labeling

Computational Linguistics
The importance of syntactic parsing and inference in semantic role labeling

Computational Linguistics
'Deep' grammatical relations for semantic interpretation

CrossParser '08 Coling 2008: Proceedings of the workshop on Cross-Framework and Cross-Domain Parser Evaluation
Extracting a verb lexicon for deep parsing from FrameNet

DeepLP '07 Proceedings of the Workshop on Deep Linguistic Processing
A lightweight semantic chunking model based on tagging

HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
The necessity of syntactic parsing for semantic role labeling

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Who, what, when, where, why?: comparing multiple approaches to the cross-lingual 5W task

ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Exploration of the LTAG-spinal formalism and Treebank for semantic role labeling

GEAF '09 Proceedings of the 2009 Workshop on Grammar Engineering Across Frameworks
HPSG supertagging: a sequence labeling view

IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Syntactic and semantic role labeling for Chinese framenet based on cascaded conditional random fields

FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Fast query for large treebanks

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A simple approach for HPSG supertagging using dependency information

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
The revised Arabic PropBank

LAW IV '10 Proceedings of the Fourth Linguistic Annotation Workshop
Forest-guided supertagger training

COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Combining constituent and dependency syntactic views for Chinese semantic role labeling

COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Semantic role labeling using maximum entropy

CIS'04 Proceedings of the First international conference on Computational and Information Science
A syntax and semantics linking algorithm for the chinese language

TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
Using semantic roles to improve summaries

ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation

Quantified Score

Hi-index	0.00

Visualization

Abstract

We use deep linguistic features to predict semantic roles on syntactic arguments, and show that these perform considerably better than surface-oriented features. We also show that predicting labels from a "lightweight" parser that generates deep syntactic features performs comparably to using a full parser that generates only surface syntactic features.