Paper: A Statistical NLG Framework for Aggregated Planning and Realization

ACL ID P13-1138
Title A Statistical NLG Framework for Aggregated Planning and Realization
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

We present a hybrid natural language gen- eration (NLG) system that consolidates macro and micro planning and surface re- alization tasks into one statistical learn- ing process. Our novel approach is based on deriving a template bank automatically from a corpus of texts from a target do- main. First, we identify domain specific entity tags and Discourse Representation Structures on a per sentence basis. Each sentence is then organized into semanti- cally similar groups (representing a do- main specific concept) by k-means cluster- ing. After this semi-automatic processing (human review of cluster assignments), a number of corpus?level statistics are com- piled and used as features by a ranking SVM to develop model weights from a training corpus. At generation time, a set of input data, th...