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<pdf width="1500px">https://ceur-ws.org/Vol-1660/invited1.pdf</pdf>
<pre>
  Finding Meaning: The Missing Link
 Between Natural Language and Formal
              Ontology
                                  Brandon BENNETT a,1
              a Institute for Artificial Intelligence and Biological Systems

                     School of Computing, University of Leeds, UK

          Abstract. The obvious starting point for investigating meaning is the analysis of
          natural languages and their usage. Even from ancient times, examination of rea-
          soning expressed in natural language revealed that patterns of valid inference of-
          ten follow certain patterns. Moreover, these can be expressed as formal rules that
          are idealisations of actual natural language arguments (e.g. Aristotle’s syllogisms).
          Subsequent development of artificial symbolic languages and denotational seman-
          tics have lead to formal representations that are completely precise in terms of their
          truth conditions and rules of valid inference.
             In parallel to this mathematical approach to semantics, linguists and cognitive
          scientists have continued to be interested in actual language usage. Empirical inves-
          tigations strongly indicate that natural languages operate in ways that are far less
          precise and less constrained than formal languages. In particular, natural language
          terminology is very often vague and ambiguous, and its interpretation often highly
          dependent on contextual factors. Hence, many linguists prefer to describe language,
          in terms of statistical properties of linguistic tokens occurring within corpora of
          language use examples, rather than in terms of a formal representation.
             More recently the requirements of information technology have lead to the con-
          struction of “formal ontologies”, which seek to capture the meanings of linguistic
          terms by means of axioms and/or definitions expressed using a formal language. In
          its most naive form, an ontology simply identifies each of a set of natural language
          words with a symbol in a formal language. But of course this is problematic, be-
          cause the formal language is not equipped to deal with the ambiguity, vagueness or
          context sensitivity that may affect the interpretation of the term.
             My talk will explore ways that formal ontology can be reunited with empirical
          investigations of language usage. I will suggest that establishing a relationship be-
          tween natural language terminology and a formalised representation requires sev-
          eral aspects of semantic variability to be taken into account. This requires both ex-
          tension of the formal apparatus associated with an ontology and also empirical, sta-
          tistical information about the usage of linguistic terms. I outline my own approach
          which using my “Statistical Standpoint Semantics” to incorporate variability into a
          formal language and “Corpus Guided Sense Cluster Analysis” to establish a map-
          ping between linguistic terms and formal symbols.




1 e-mail: brandon@comp.leeds.ac.uk

</pre>