Text-to-text surface realisation using dependency-tree replacement

Authors:
Eder Miranda De Novais;Thiago Dias Tadeu;Ivandré Paraboni
Affiliations:
School of Arts, Sciences and Humanities, University of São Paulo, EACH, São Paulo, Brazil;School of Arts, Sciences and Humanities, University of São Paulo, EACH, São Paulo, Brazil;School of Arts, Sciences and Humanities, University of São Paulo, EACH, São Paulo, Brazil
Venue:
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Year:
2010

Citing 8
Cited 0

An augmented template-based approach to text realization

Natural Language Engineering
Forest-based statistical sentence generation

NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Corpus-based lexical choice in natural language generation

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Stochastic language generation for spoken dialogue systems

ANLP/NAACL-ConvSyst '00 Proceedings of the 2000 ANLP/NAACL Workshop on Conversational systems - Volume 3
Real versus Template-Based Natural Language Generation: A False Opposition?

Computational Linguistics
Statistical Surface Realisation of Portuguese Referring Expressions

GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
An architecture for data-to-text systems

ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation
SimpleNLG: a realisation engine for practical applications

ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Surface realisation - the task of producing word strings from non-linguistic input data - has been the focus of a great deal of research in the field of data-to-text Natural Language Generation (NLG). In this work we discuss an alternative approach to surface realisation, in which we borrow NLG techniques from the sister field of text-to-text generation to implement text generation based on examples in natural language. Our approach is suitable to simpler applications that are not linguistically-oriented by design, and which may be able to provide only minimal input knowledge to the NLG module.