Explorations in lexical sample and all-words lexical substitution

In this paper, we experiment with several techniques to solve the problem of lexical substitution, both in a lexical sample as well as an all-words setting, and compare the benefits of combining multiple lexical resources using both unsupervised and supervised approaches. Overall in the lexical sample setting, the results obtained through the combination of several resources exceed the current state-of-the-art when selecting the best substitute for a given target word, and place second when selecting the top ten substitutes, thus demonstrating the usefulness of the approach. Further, we put forth a novel exploration in all-words lexical substitution and set ground for further explorations of this more generalized setting.