Just like to clarify that this goes beyond a rule-based system. Rules can get you pretty far[1] but this improves on that by intelligently discounting the bad rules using weak supervision techniques. The end result here is a pile of labeled data which you train your model on. The model trained on this data can generalise well beyond those labels.
[1]: Aside: working at Alexa, I was surprised that something like 80% of utterances were covered by rules rather than an ML model. People have learned to use Alexa for a small handful of things and you can cover those fairly well using a way to generate rules from phrase patterns and catalogs of nouns.
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Just like to clarify that this goes beyond a rule-based system. Rules can get you pretty far[1] but this improves on that by intelligently discounting the bad rules using weak supervision techniques. The end result here is a pile of labeled data which you train your model on. The model trained on this data can generalise well beyond those labels.
[1]: Aside: working at Alexa, I was surprised that something like 80% of utterances were covered by rules rather than an ML model. People have learned to use Alexa for a small handful of things and you can cover those fairly well using a way to generate rules from phrase patterns and catalogs of nouns.