Automatic Prediction of Discourse Connectives
Eric Malmi, Daniele Pighin, Sebastian Krause, MIKHAIL V. KOZHEVNIKOV · 2018
Accurate prediction of suitable discourse connectives (however, furthermore, etc.) is a key component of any system aimed at building coherent and fluent discourses from shorter sentences and passages.As an example, a dialog system might assemble a long and informative answer by sampling passages extracted from different documents retrieved from the Web.We formulate the task of discourse connective prediction and release a dataset of 2.9M sentence pairs separated by discourse connectives for this task.Then, we evaluate the hardness of the task for human raters, apply a recently proposed decomposable attention (DA) model to this task and observe that the automatic predictor has a higher F1 than human raters (32 vs. 30).Nevertheless, under specific conditions the raters still outperform the DA model, suggesting that there is headroom for future improvements.