Abstract
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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Pan, S., Shaw, J. (2004). SEGUE: A Hybrid Case-Based Surface Natural Language Generator. In: Belz, A., Evans, R., Piwek, P. (eds) Natural Language Generation. INLG 2004. Lecture Notes in Computer Science(), vol 3123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27823-8_14
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DOI: https://doi.org/10.1007/978-3-540-27823-8_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22340-5
Online ISBN: 978-3-540-27823-8
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