Geometry of Compositionality
Table 2: Accuracy values (%) for Experiment I: Compositionality detection from contexts
['[EMPTY]', 'English (CBOW)', 'English (MSSG)', 'Chinese (CBOW)', 'Chinese (MSSG)']
Detection Results: We used both average and PCA subspace representations for the target phrase and its context. Since the average vector representation is commonly used in recent works, we take “avg phrase + avg context” as our baseline. We note that having a PCA approximation for both the phrase and the context, and the use of MSSG embedding yielded the best accuracy for this task in both the English and the Chinese datasets; this is an instance where the PCA subspace representation is superior to the average representation. We believe that unsupervised improvement beyond the fairly high accuracy rates is likely to require substantially new ideas as compared to those in this paper.