Comment by brockf

Most implementations are actually moving in the opposite direction. Previously, there was a tendency to look to aggregate words into phrases to better capture the "context" of a word. Now, most approaches are splitting words into sub-word parts or even characters. With networks that capture temporal relationships across tokens (as opposed to older, "bag of words" models), multi-word patterns can effectively be captured by attending to the temporal order of sub-word parts.