19 January 2017, Computational Linguistics Seminar, Gemma Boleda
Over a century ago, Frege famously introduced the distinction between sense and reference that is one of the theoretical foundations of formal semantics. However, in practice formal semanticists took reference and ran away with it, either eschewing sense-related issues altogether or giving a referential treatment to them (with notable exceptions). In this talk, I argue that we need to go back to Fregean sense, and propose that data-induced, continuous representations provided by distributional semantics and deep learning methods provide a good methodological handle for sense-related aspects of meaning. I support these claims with results from both computational modeling and theoretical studies. I then revisit reference and present ongoing work on the challenging enterprise of tackling it with continuous methods, too.