[Arxiv 1703.04368] Symbol Grounding via Chaining of Morphisms
In [1] I commented about pregroup grammar and word2vec (distributional) unification being seriously worked on in Clark and Coecke via tensor nets categorically, and in a comment to [2] ('Towards deep symbolic reinforcement learning'), I liked the use of unsupervised learning (there visual autoencoders) to nucleate concepts that grounded symbols.
Two independent comments, leaving behind the need of a vertical picture subsuming both lines of thought. I can't say this paper is a solution to this harmonization problem, but It seems to tackle some aspects of it.
[1] https://www.reddit.com/r/LanguageTechnology/comments/5kzn70/starting_in_semantic_parsing_is_ccg_still_relevant/dbs0zg1/
[2] https://news.ycombinator.com/item?id=12713436