>It could be concubine, for example. Precisely. Models which use this space do not propose strong equality (==). Rather, they would output a series of probabil

>It could be concubine, for example. Precisely. Models which use this space do not propose strong equality (==). Rather, they would output a series of probabilities, and choose the most likely. Stating king + woman = queen + man is somewhat disingenuous; what should be said (mathematically) is something like the following: the word lying closest to the vector vec('king') + vec('woman') - vec('man') is 'queen'. To suggest that a NN can't learn something about the meaning of words from a large corpus of text is unsubstantiated, I believe. The statement above suggests they do, I would say. I would not be too surprised if a sufficiently complex NN could 'learn' the concept of gender with a corpus of English text to a decently high degree of accuracy, simply based on vestigial features left from French and Old English.