DISTRIBUTION AND INFERENCE: WHAT PHILOSOPHICAL AND COMPUTATIONAL SEMANTICS CAN LEARN FROM EACH OTHER

Distribution of a word across contexts has proved to be a very useful approximation of the word’s meaning. This paper reflects on the recent attempts to enhance distributional (or vector space) semantics of words with meaning composition, in particular with Fregean compositionality. The author discusses the nature and performance of distributional semantic representations and argues against the thesis that semantics is in some sense identical with distribution. Instead he proposes that distribution is merely a reflection of semantics, and a substantially imperfect one. That raises some doubts regarding the very idea of obtaining semantic representations for larger wholes (phrases, sentences) by combining the distributional representations of particular items. In any case, the author rejects the generally unquestioned assumption that formal semantics provides a good theory of semantic composition, which it would be desirable to combine with distributional semantics (as a theory that is highly successful on the lexical field). He suggests that a positive alternative to the strong reading of the distributional hypothesis can be seen in the philosophy of inferentialism with respect to language meaning. The author argues that the spirit of inferentialism is reasonably compatible with the current practice of distributional semantics, and he discusses the motivations for as well as the obstacles in the way of implementing the philosophical position in a computational framework.