Automatic Prediction of Discourse Connectives

Autor:	Malmi, Eric, Pighin, Daniele, Krause, Sebastian, Kozhevnikov, Mikhail
Rok vydání:	2017
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	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. Comment: This is a pre-print of an article appearing at LREC 2018
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1702.00992 Zobrazit plný text záznamu View this record from Arxiv