Natural Language Generation Using Link Grammar for General Conversational Intelligence
This addresses the issue of lacking general conversational intelligence in AGI and NLP systems, enabling automated and understandable natural language generation without manual customization.
The paper tackles the problem of generating grammatically valid sentences for general conversational intelligence by proposing a new technique using the Link Grammar database, which far outperforms current state-of-the-art baselines.
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.