Evaluating Neural Word Representations inTensor-Based Compositional Settings
Table 1: Word co-occurrence frequencies extracted from the BNC [Leech et al.1994].
['[EMPTY]', 'philosophy', 'book', 'school']
The words philosophy, book and school signify vector space dimensions. As the vector for John is closer to Mary than it is to idea in the vector space—a direct consequence of the fact that John’s contexts are similar to Mary’s and dissimilar to idea’s—we can infer that John is semantically more similar to Mary than to idea.