DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion
Table 9: Alignment-based connective prediction accuracy for the most common connectives. When a model did not add a connective, the token ⟨other⟩ is used.
['Connective', 'DfSport', 'DfWiki', 'Top 3 connectives']
We start by considering the semantic relation between the input sentences. We observe that when the model predicts a wrong connective, that connective is often reasonable, e.g., predicting “but” instead of “and” or “however”. Moreover, a second source of error is not adding a connective at all. It is also clear that some connectives, like “however”, “ although” and “for example”, are harder to learn.