Speaker
Affilliation
Edinburgh
Abstract
Traditional vector-based models use word co-occurrence counts from large corpora to represent lexical meaning. In this talk we present a novel framework for constructing semantic spaces that takes syntactic relations into account. We introduce a formalisation for this class of models which allows linguistic knowledge to guide the construction of semantic spaces. We evaluate our framework on tasks that are relevant for cognitive science and NLP: semantic priming, lexicon acquisition and word sense disambiguation. In all cases we show that our framework obtains results that are comparable or superior to state-of-the art.