Question Answering
Contributors:
- Diego Collarana (FIT)
- Michael Wetzel (Coreon)
- Daniel Baldassare (doctima)
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Draft from Daniel Baldassare
Definition/Description: Question answering is one of the main application field of large language models. Knowledge graphs have been shown to be useful for providing answers to questions about specific domains and improving the performance of LLM. This chapter covers:
- Methods to retrieve relevant data in the KG
- Methods to rerank the retrieved data from the KG
- Advanced prompt techniques like Chain-of-Thought, Tree of Thoughts (ToT) and Graph of Thoughts (GoT) to handle complex questions
Literature:
Towards Improving the Performance of Question Answering System using Knowledge Graph - A Survey
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
Fact Checking
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- Diego Collarana (FIT)
- Daniel Baldassare (doctima)
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- Diego Collarana (FIT)
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