Building natural language generation systems
Building natural language generation systems
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
The rhetorical parsing, summarization, and generation of natural language texts
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A fast and portable realizer for text generation systems
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Learning features that predict cue usage
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Natural language generation in dialog systems
HLT '01 Proceedings of the first international conference on Human language technology research
Sentence Fusion for Multidocument News Summarization
Computational Linguistics
Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Trainable sentence planning for complex information presentation in spoken dialog systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Supplementing Entity Coherence with Local Rhetorical Relations for Information Ordering
Journal of Logic, Language and Information
SimpleNLG: a realisation engine for practical applications
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
Learning contrastive connectives in sentence realization ranking
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
Individual and domain adaptation in sentence planning for dialogue
Journal of Artificial Intelligence Research
Computer Speech and Language
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The freely available SPaRKy sentence planner uses hand-written weighted rules for sentence plan construction, and a user-or domain-specific second-stage ranker for sentence plan selection. However, coming up with sentence plan construction rules for a new domain can be difficult. In this paper, we automatically extract sentence plan construction rules from the RST-DT corpus. In our rules, we use only domain-independent features that are available to a sentence planner at runtime. We evaluate these rules, and outline ways in which they can be used for sentence planning. We have integrated them into a revised version of SPaRKy.