Natural Language Generation systems typically have two parts - strategic ('what to say') and tactical ('how to say'). We present our experiments in building an unsupervised corpus-driven template based tactical NLG system. We consider templates as a sequence of words containing gaps. Our idea is based on the observation that templates are grammatical locally (within their textual span). We posit the construction of a sentence as a highly restricted sequence of such templates. This work is an attempt to explore the resulting search space using Genetic Algorithms to arrive at acceptable solutions. We present a baseline implementation of this approach which outputs gapped text.
@article{arxiv.1605.07366,
title = {Experiments in Linear Template Combination using Genetic Algorithms},
author = {Nikhilesh Bhatnagar and Radhika Mamidi},
journal= {arXiv preprint arXiv:1605.07366},
year = {2016}
}