We are exploring techniques to store fixed embeddings dynamically, so that the non-compositional phrases can be selected as part of the end-to-end training.
compositional Representation the non-compositional embeddings above only account for a subset of all n-grams, so we additionally construct compositional embeddings for each chunk by running a BiLSTM encoder over the individual embeddings of each unit-level token within it (Dyer et al., 2016).