Natural Language Generation through Case-Based Text Modification

  • Josep Valls
  • Santiago Ontañón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7466)


Natural Language Generation (NLG) is one of the longstanding problems in Artificial Intelligence. In this paper, we focus on a subproblem in NLG, namely surface realization through text modification: given a source sentence and a desired change, produce a grammatically correct and semantically coherent sentence that implements the desired change. Text modification has many applications within text generation like interactive narrative systems, where stories tailored to specific users are generated by adapting or instantiating a pre-authored story. We present a case-based approach where cases correspond to pairs of sentences implementing specific modifications. We describe our retrieval, adaptation and revise procedures. The main contribution of this paper is an approach to perform case-adaptation in textual domains.


Ground Truth Language Model Candidate Solution Surface Realization Target Sentence 
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 2012

Authors and Affiliations

  • Josep Valls
    • 1
  • Santiago Ontañón
    • 1
  1. 1.Computer Science DepartmentDrexel UniversityPhiladelphiaUSA

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