Automatic Summarization Based on Sentence Morpho-Syntactic Structure: Narrative Sentences Compression

We propose an automated text summarization through sentence compression. Our approach uses constituent syntactic function and position in the sentence syntactic tree. We first define the idea of a constituent as well as its role as an information provider, before analyzing contents and discourse consistency losses caused by deleting such a constituent. We explain why our method works best with narrative texts. With a rule-based system using SYGFRAN’s morphosyntactic analysis for French [1], we select removable constituents. Our results are satisfactory at the sentence level but less effective at the whole text level, a situation we explain by describing the difference of impact between constituents and relations.