Inferring Grammars for Mildly Context Sensitive Languages in Polynomial-Time

  • Tim Oates
  • Tom Armstrong
  • Leonor Becerra Bonache
  • Mike Atamas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4201)


Natural languages contain regular, context-free, and context-sensitive syntactic constructions, yet none of these classes of formal languages can be identified in the limit from positive examples. Mildly context-sensitive languages are able to represent some context-sensitive constructions, those most common in natural languages, such as multiple agreement, crossed agreement, and duplication. These languages are attractive for natural language applications due to their expressiveness, and the fact that they are not fully context-sensitive should lead to computational advantages as well. We realize one such computational advantage by presenting the first polynomial-time algorithm for inferring Simple External Context Grammars, a class of mildly context-sensitive grammars, from positive examples.


Natural Language Regular Language Bijective Mapping Computational Advantage Lexical Semantic 
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 2006

Authors and Affiliations

  • Tim Oates
    • 1
  • Tom Armstrong
    • 1
  • Leonor Becerra Bonache
    • 2
  • Mike Atamas
    • 1
  1. 1.University of Maryland Baltimore CountyBaltimoreUSA
  2. 2.Rovira i Virgili UniversityTarragonaSpain

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