Here is the full dialog, in case you are still interested.
[Bob posts a problem about data classification]
Alice: You should use LLM. It especially suites your problem
Bob: In my understanding LLM is only strong where the context is large. If the context is small then using regex gives better result? Also, regex has advantages of high accuracy, fast, understandable and debuggable?
Alice: Not really. Also, regex cannot work with synonyms and it must be in form. LLM is trained on multiple data, so if you make good prompt then it’s much better
Bob: But the nature of catching synonyms is still depending on context. As the context is small then there is not much synonyms at the beginning. If even human cannot get them then how can machine recognize them?
Alice: You should try it first. You are reasoning too much
There are some notes:
By “regex” Bob actually means rule-based approach. He thought in the context of NLP people generally understand regex and rule-based approach as one
He mistakes synonym with homonym. Had he been aware of that he might have not said “the nature of catching synonyms is still depending on context”
Here is the full dialog, in case you are still interested.
[Bob posts a problem about data classification]
Alice: You should use LLM. It especially suites your problem
Bob: In my understanding LLM is only strong where the context is large. If the context is small then using regex gives better result? Also, regex has advantages of high accuracy, fast, understandable and debuggable?
Alice: Not really. Also, regex cannot work with synonyms and it must be in form. LLM is trained on multiple data, so if you make good prompt then it’s much better
Bob: But the nature of catching synonyms is still depending on context. As the context is small then there is not much synonyms at the beginning. If even human cannot get them then how can machine recognize them?
Alice: You should try it first. You are reasoning too much
There are some notes:
By “regex” Bob actually means rule-based approach. He thought in the context of NLP people generally understand regex and rule-based approach as one
He mistakes synonym with homonym. Had he been aware of that he might have not said “the nature of catching synonyms is still depending on context”
These info are only revealed later on.