From a Lexical to a Semantic Distributional Hypothesis
Luigi Di, Guido Boella, Alice Ruggeri, Loredana Cupi, John Adebayo Kolawole, Livio Robaldo · Accademia University Press eBooks · 2015
Distributional Semantics is based on the idea of extracting semantic information from lexical information in (multilingual) corpora using statistical algorithms. This paper presents the challenging aim of the SemBurst research project1 which applies distributional methods not only to words, but to sets of semantic information taken from existing semantic resources and associated with words in syntactic contexts. The idea is to inject semantics into vector space models to find correlations between statements (rather than between words). The proposal may have strong impact on key applications such as Word Sense Disambiguation, Textual Entailment, and others.