Common Sense Inference Using Verb Valency Frames

  • Zuzana Nevěřilová
  • Marek Grác
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7499)


In this paper we discuss common-sense reasoning from verb valency frames. While seeing verbs as predicates is not a new approach, processing inference as a transformation of valency frames is a promising method we developed with the help of large verb valency lexicons. We went through the whole process and evaluated it on several levels: parsing, valency assignment, syntactic transformation, syntactic and semantic evaluation of the generated propositions.

We have chosen the domain of cooking recipes. We built a corpus with marked noun phrases, verb phrases and dependencies among them. We have manually created a basic set of inference rules and used it to infer new propositions from the corpus. Next, we extended this basic set and repeated the process. At first, we generated 1,738 sentences from 175 rules. 1,633 sentences were judged as (syntactically) correct and 1,533 were judged as (semantically) true. After extending the basic rule set we generated 2,826 propositions using 276 rules. 2,598 propositions were judged correct and 2,433 of the propositions were judged true.


Noun Phrase Inference Rule Semantic Role Syntactic Rule Syntactic Property 
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

  • Zuzana Nevěřilová
    • 1
  • Marek Grác
    • 1
  1. 1.NLP Centre, Faculty of InformaticsMasaryk UniversityBrnoCzech Republic

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