Paper Info
Title
Let'S Do It "Again": A First Computational Approach To Detecting Adverbial Presupposition Triggers
Abstract
We introduce the task of predicting adverbial presupposition triggers such as also and again. Solving such a task requires detecting recurring or similar events in the discourse context, and has applications in natural language generation tasks such as summarization and dialogue systems. We create two new datasets for the task, derived from the Penn Treebank and the Annotated English Gigaword corpora, as well as a novel attention mechanism tailored to this task. Our attention mechanism augments a baseline recurrent neural network without the need for additional trainable parameters, minimizing the added computational cost of our mechanism. We demonstrate that our model statistically outperforms a number of baselines, including an LSTM-based language model.
Year
DOI
Venue
2018
10.18653/v1/p18-1256
PROCEEDINGS OF THE 56TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL), VOL 1
Field
DocType
Volume
Natural language generation,Automatic summarization,Adverbial,Computer science,Presupposition,Recurrent neural network,Artificial intelligence,Treebank,Natural language processing,Language model
Journal
abs/1806.04262
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Andre Cianflone101.69
Yulan Feng201.35
Jad Kabbara301.01
Jackie Chi Kit Cheung47016.92