MUSE: Modularizing Unsupervised Sense Embeddings
Table 1: Spearman’s rank correlation ρ x100 on the SCWS dataset. † denotes superior performance to all unsupervised competitors.
['[BOLD] Method', '[BOLD] MaxSimC', '[BOLD] AvgSimC']
The embedding sizes of all baselines are 300, except 50 in Huang et al. Here we report the setting for baselines based on the best average performance in this task. We also show the performance of supervised sense embeddings as an upperbound of unsupervised methods due to the usage of additional supervised information from WordNet.