  Many current artificial general intelligence (AGI) and natural language
processing (NLP) architectures do not possess general conversational
intelligence--that is, they either do not deal with language or are unable to
convey knowledge in a form similar to the human language without manual,
labor-intensive methods such as template-based customization. In this paper, we
propose a new technique to automatically generate grammatically valid sentences
using the Link Grammar database. This natural language generation method far
outperforms current state-of-the-art baselines and may serve as the final
component in a proto-AGI question answering pipeline that understandably
handles natural language material.
