BIO tagging

A labeling scheme that marks the Beginning, Inside, and Outside of each named span.

tokens -> [B-TYPE | I-TYPE | O] per token (e.g. New=B-LOC York=I-LOC)

BIO tagging is the standard way to turn span-finding (like named entity recognition) into a per-token classification: each token is labeled B- (begins an entity), I- (inside/continues one), or O (outside any entity). This cleanly handles multi-word names — 'New' gets B-LOC and 'York' gets I-LOC — and marks exactly where each entity starts and stops. An encoder predicts one of these tags for every token from its contextual embedding.

Appears in

Put it to work Masked Language Models · pt 5

Nearby in the brain

[CLS] token contextual embedding encoder fine-tuning named entity recognition natural language inference sequence classification transfer learning