Encoding Commonsense Lexical Knowledge into WordNet

In this paper, we propose an extension of the WordNet conceptual model, with the final purpose of encoding the common sense lexical knowledge associated to words used in everyday life. The extended model has been defined starting from the short descriptions generated by naïve speakers in relation to target concepts (i.e. feature norms). Even if this proposal has been developed primarily for therapeutic purposes, it can be seen as a generalization of the original WordNet model that takes into account a much wider and systematic set of semantic relations. The extended model is also an enhancement of the psycholinguistic vocation of the WordNet model. A featural representation of concepts is nowadays assumed by most models of the human semantic memory. For testing our proposal, we conducted a feature elicitation experiment and collected descriptions of 50 concepts from 60 participants. Problematic issues related to the encoding of this information into WordNet are discussed and preliminary results are presented.

[1]  Max J. Cresswell,et al.  A New Introduction to Modal Logic , 1998 .

[2]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[3]  G. Miller,et al.  A Semantic Network of English Verbs , 1998 .

[4]  Antonietta Alonge,et al.  The linguistic design of the EuroWordNet database , 1998 .

[5]  Christiane Fellbaum,et al.  A Semantic Network of English: The Mother of All WordNets , 1998, Comput. Humanit..

[6]  Christiane Fellbaum,et al.  Nouns in WordNet , 1998 .

[7]  M. L. Lambon Ralph,et al.  Prototypicality, distinctiveness, and intercorrelation: Analyses of the semantic attributes of living and nonliving concepts , 2001, Cognitive neuropsychology.

[8]  Emanuele Pianta,et al.  Revising the Wordnet Domains Hierarchy: semantics, coverage and balancing , 2004 .

[9]  Emanuele Pianta,et al.  Extending WordNet with Syntagmatic Information , 2004 .

[10]  Mark S. Seidenberg,et al.  Semantic feature production norms for a large set of living and nonliving things , 2005, Behavior research methods.

[11]  German Rigau,et al.  Exploring the Automatic Selection of Basic Level Concepts , 2006 .

[12]  Wolf Vanpaemel,et al.  Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts , 2008, Behavior research methods.

[13]  David P Vinson,et al.  Semantic feature production norms for a large set of objects and events , 2008, Behavior research methods.

[14]  Emanuele Pianta,et al.  A Feature Type Classification for Therapeutic Purposes: A Preliminary Evaluation with Non-Expert Speakers , 2010, Linguistic Annotation Workshop.

[15]  Emanuele Pianta,et al.  Exploiting Lexical Resources for Therapeutic Purposes: the Case of WordNet and STaRS.sys , 2010 .

[16]  Marco Baroni,et al.  A set of semantic norms for German and Italian , 2011, Behavior research methods.