SEGUE: A Hybrid Case-Based Surface Natural Language Generator

  • Shimei Pan
  • James Shaw
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3123)


This paper presents Segue, a hybrid surface natural language generator that employs case-based paradigm but performs rule-based adaptations. It uses an annotated corpus as its knowledge source and employs grammatical rules to construct new sentences. By using adaptation-guided retrieval to select cases that can be adapted easily to the desired output, Segue simplifies the process and avoids generating ungrammatical sentences. The evaluation results show the system generates grammatically correct sentences (91%), but disfluency is still an issue.


Machine Translation Retrieval Phase Insertion Operator Annotate Corpus Grammatical Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Shimei Pan
    • 1
  • James Shaw
    • 1
  1. 1.IBM T.J. Watson Research CenterHawthorneUSA

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