Triple

T22802041
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best Picture (for Driving Miss Daisy, as director of winning film) E564420 entity
Predicate notableDistinction P22 FINISHED
Object one of the few Best Picture winners whose director was not nominated for Best Director 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: one of the few Best Picture winners whose director was not nominated for Best Director | Statement: [Academy Award for Best Picture (for Driving Miss Daisy, as director of winning film), notableDistinction, one of the few Best Picture winners whose director was not nominated for Best Director]

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_69e245823f4c8190ade442cdcc2c224a completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cdd87648190ba30f0b8f3ef7346 completed April 29, 2026, 3:37 a.m.
Created at: April 17, 2026, 3:31 p.m.