Triple

T6317205
Position Surface form Disambiguated ID Type / Status
Subject Bob Knight E141645 entity
Predicate occupation P3 FINISHED
Object television analyst LITERAL FINISHED

How this triple was built (1 step)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: television analyst | Statement: [Bob Knight, occupation, television analyst]

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c008d13b8c8190be47d896eb735605 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c064c25530819080b29e0029175c00 completed March 22, 2026, 9:53 p.m.
Created at: March 22, 2026, 4:29 p.m.