Chain of thought and annotation

[Lj Miranda]

• Faithful chain-of-thought reasoning
• Chain of thought prompting elicits reasoning in large language models
• Is GPT-3 a good data annotator?
• Turn LLM into knowledge base

[Lj Miranda]

Maybe...follow how the google paper constructs their chain of thought prompts?
Current unknowns:

• What's the difference between CoT and few-shot? Former is a process and latter are i.i.d. examples?
• What's the benefit of CoT in annotation? Maybe there's an HCI angle? (find decryzinski paper)
• Can I do this without using ChatGPT? Like use GPT-J or BLOOM or any open-source LLM?

[Lj Miranda]

I remember an idea that annotator disagreements are also nice signals (of what?). Maybe there's something there.

[Lj Miranda]

How about, in the future, use langchain to feed an annotation guideline (ACE2004/The Guardian), then let the LLM show the exact passage as to why that was the case. Then you can kinda verify it

https://github.com/hwchase17/langchain