Paper: Forest-Based Statistical Sentence Generation

ACL ID A00-2023
Title Forest-Based Statistical Sentence Generation
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors

This paper presents a new approach to sta- tistical sentence generation in which Mterna- tive phrases are represented as packed sets of trees, or forests, and then ranked statistically to choose the best one. This representation offers advantages in compactness and in the ability to represent syntactic information. It also fa- cilitates more efficient statistical ranking than a previous approach to statistical generation. An efficient ranking algorithm is described, to- gether with experimental results showing signif- icant improvements over simple enumeration or a lattice-based approach.