SEGUE: A Hybrid Case-Based Surface Natural Language Generator

نویسندگان

  • Shimei Pan
  • James Shaw
چکیده

This paper presents Segue, a hybrid surface natural language generator that employs case-based paradigm but performs rulebased 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

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تاریخ انتشار 2004