Enhancing the Expression of Contrast in the SPaRKy Restaurant Corpus


We show that Nakatsu & White’s (2010) proposed enhancements to the SPaRKy Restaurant Corpus (SRC; Walker et al., 2007) for better expressing contrast do indeed make it possible to generate better texts, including ones that make effective and varied use of contrastive connectives and discourse adverbials. After first presenting a validation experiment for naturalness ratings of SRC texts gathered using Amazon’s Mechanical Turk, we present an initial experiment suggesting that such ratings can be used to train a realization ranker that enables higher-rated texts to be selected when the ranker is trained on a sample of generated restaurant recommendations with the contrast enhancements than without them. We conclude with a discussion of possible ways of improving the ranker in future work.

In Proc. of the 14th European Workshop on Natural Language Generation.