Paper: Inducing Document Plans for Concept-to-Text Generation

ACL ID D13-1157
Title Inducing Document Plans for Concept-to-Text Generation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

In a language generation system, a content planner selects which elements must be in- cluded in the output text and the ordering be- tween them. Recent empirical approaches per- form content selection without any ordering and have thus no means to ensure that the out- put is coherent. In this paper we focus on the problem of generating text from a database and present a trainable end-to-end generation system that includes both content selection and ordering. Content plans are represented intuitively by a set of grammar rules that op- erate on the document level and are acquired automatically from training data. We de- velop two approaches: the first one is inspired from Rhetorical Structure Theory and repre- sents the document as a tree of discourse re- lations between database records; th...