Inducing clause-combining rules: A case study with the SParKy Restaurant Corpus

Abstract

We describe an algorithm for inducing clause-combining rules for use in a traditional natural language generation architecture. An experiment pairing lexicalized text plans from the SPaRKy Restaurant Corpus with logical forms obtained by parsing the corresponding sentences demonstrates that the approach is able to learn clause-combining operations which have essentially the same coverage as those used in the SPaRKy Restaurant Corpus. This paper fills a gap in the literature, showing that it is possible to learn microplanning rules for both aggregation and discourse connective insertion, an important step towards ameliorating the knowledge acquisition bottleneck for NLG systems that produce texts with rich discourse structures using traditional architectures.