Comments (1)
Hi @ChakshuGautam . There can be 2 approaches to solve this, the first one involving LLMs, langchains and things like OpenAI call agents but I feel this might be an overkill for now.
The second one which I was thinking might be more suitable at the moment.
It involves first
- preprocessing the dataset to extract individual sentences or segments of text
- We can then use named entity recognition (NER), keyword extraction, or topic modeling to identify important elements in the text.
- We segment the text into smaller portions based on the identified key concepts
- We employ some transformer based model to generate question based on the small text portion
- We use paraphrasing techniques to vary the wording of the questions generated
- We make validation metrics such as overlap and sentence coverage.
Would like to discuss more and get your opinions.
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