Has anyone done any work on handing words that have overloading meanings? Something like 'lead' has two really distinct uses. It's really multiple words that happened to be spelt the same.
My experience is that you can distinguish word senses, but it seems the data isn't good enough to improve anything but a task that specifically evaluates that same vocabulary of word senses.
I see a sibling comment with link to spaCy's sense2vec, which uses the coarsest possible senses -- one sense for nouns, one sense for verbs, one sense for proper nouns, etc. It's a start.