Since this appears to be the 'related works' thread, I'll add my links here. A reasonable amount of work has already been done in disambiguation of the meaning

Since this appears to be the 'related works' thread, I'll add my links here. A reasonable amount of work has already been done in disambiguation of the meanings of words with word embeddings, some of it trained, some untrained. These particular papers that have recently caught my attention, and have the potential to bring significant gains wrt existing technologies are these: 1. Infinite-Length Word embeddings http://arxiv.org/pdf/1511.05392v2.pdf http://arxiv.org/pdf/1511.05392v2.pdf I am particularly excited about this paper, as the authors suggest a method to create variable-length word vectors, depending on the multiplicity of meanings a word can have (so theoretically, if a word had a _lot_ of meanings, the word vectors would me very large. Reminds one of the word 'Aladeen'). IF the authors happen to me hanging out here, the community is eagerly waiting for the reference implementation. : ) 2. Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing http://jmlr.csail.mit.edu/proceedings/papers/v22/bordes12/bordes12.pdf http://jmlr.csail.mit.edu/proceedings/papers/v22/bordes12/bo... 3. Breaking Sticks And Ambiguities With Adaptive Skip-Gram http://arxiv.org/pdf/1502.07257v2.pdf http://arxiv.org/pdf/1502.07257v2.pdf Edit: added paper 3.