Wide-Coverage Parsing, Semantics, and Morphology

  • Ruket ÇakıcıEmail author
  • Mark Steedman
  • Cem Bozşahin
Part of the Theory and Applications of Natural Language Processing book series (NLP)


Wide-coverage parsing poses three demands: broad coverage over preferably free text, depth in semantic representation for purposes such as inference in question answering, and computational efficiency. We show for Turkish that these goals are not inherently contradictory when we assign categories to sub-lexical elements in the lexicon. The presumed computational burden of processing such lexicons does not arise when we work with automata-constrained formalisms that are trainable on word-meaning correspondences at the level of predicate-argument structures for any string, which is characteristic of radically lexicalizable grammars. This is helpful in morphologically simpler languages too, where word-based parsing has been shown to benefit from sub-lexical training.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Middle East Technical UniversityAnkaraTurkey
  2. 2.University of EdinburghEdinburghUK

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