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Creating Meaningful Word Vectors and Examining their use as Representations of Word Meaning
Abstract
We identify three shortcomings of word vectors as representations of the full meaning of words: 1) the dimensions of the vectors are implicit and difficult to interpret, 2) the vectors entangle all the meanings and uses of words, and 3) the vectors are unstructured. We propose solutions to each of these shortcomings and explore the implications. Our goal is to integrate word, phrase, and clause level vectors representing fine-grained, associative aspects of meaning into grammatical analysis, to support the resolution of structural ambiguities that cannot be grammatically resolved.