The Use of Large Language Models in Combination with the Ontological Approach for the Synthesis of Natural Language Text

This research presented an approach based on the application of structured prompt instructions to large language models (LLM). Methodological foundations for using an ontology-driven system of structured prompts in interaction with ChatGPT were developed. The ChatGPT system allows expanding the knowledge base by obtaining new information from existing knowledge units based on a set of contexts. Thus, methods for generating meaningful responses in natural language were considered using a large language model using ontological approaches and natural language contexts. Using the proposed methodology, the OntoChatGPT system was developed, which effectively extracts entities from contexts, classifies them and generates appropriate responses. An experiment on the reverse synthesis of natural language sentences based on their ontological representation using large language models allows to clearly demonstrate the effectiveness of using the concept of large language models in dialogue systems. The study highlights the versatility of the methodology, emphasizing its applicability not only to ChatGPT but also to other chatbot systems based on LLMs, such as Google’s Bard utilizing the PaLM 2 LLM. The implementation of this technology is demonstrated using the Ukrainian language