"Apple sued Google over its iPhone search deal in the US." Five entities: Apple (ORG), Google (ORG), iPhone (PRODUCT), search deal (maybe), US (GPE). A good NER system extracts all of them with correct types. A bad one misses iPhone, confuses Apple the fruit with Apple the company, and labels "US" as a PERSON.
NER is the workhorse underneath every structured extraction pipeline. Resume parsing, compliance log scanning, medical record anonymization, search query understanding, grounding for chatbot responses, legal contract extraction. You never quite see it; you always depend on it.
This lesson walks the classical path (rule-based, HMM, CRF) into the modern one (BiLSTM-CRF, then transformers). Each step solves a specific limitation of the one before it. The pattern is the lesson.
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