/llm

Using LLMs to generate knowledge for NLP++

Primary LanguagePython

Leveraging Large Language Models for NLP++

Trustworthy NLP systems must be rule and knowledge based given all statistcal systems like large language models, machine learning, and neural networks are not. With the advent of large language models that can be queried about common knowledge, it is natural to use them to generate linguistic and world knowledge that can be leveraged by the NLP++ framework.

Natural Language Understanding Global Initiative (NLUGI)

The goal of NLUGI is to build the knowledge needed for mingrating linguitic and world knowledge to computers. It is a voluntary world-wide initative involving universities, industry, and individuals leveraging NLP++ for the said goal of knowldge transfer.

Local LLMs

Using locally available LLMs like Ollama allow for prompting local LLMs to generate NL responses that can be read by NLP++ analazers, transform them into NLP++ dictionaries (dict files) and knowledge bases (kbb files).