Predicting Sentence Deletions for Text Simplification Using a Functional Discourse Structure
Bohan Zhang, Prafulla Kumar Choubey, Ruihong Huang · 2022
Document-level text simplification often deletes some sentences besides performing lexical, grammatical or structural simplification to reduce text complexity.In this work, we focus on sentence deletions for text simplification and use a news genre-specific functional discourse structure, which categorizes sentences based on their contents and their function roles in telling a news story, for predicting sentence deletion.We incorporate sentence categories into a neural net model in two ways for predicting sentence deletions, either as additional features or by jointly predicting sentence deletions and sentence categories.Experimental results using human-annotated data show that incorporating the functional structure improves the recall of sentence deletion prediction by 6.5% and 10.7% respectively using the two methods, and improves the overall F1-score by 3.6% and 4.3% respectively.