Triple

T16571203
Position Surface form Disambiguated ID Type / Status
Subject Betty Gilpin E402589 entity
Predicate notableWork P4 FINISHED
Object Stuber E377781 NE FINISHED

How this triple was built (2 steps)

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: Stuber | Statement: [Betty Gilpin, notableWork, Stuber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stuber
Context triple: [Betty Gilpin, notableWork, Stuber]
  • A. Stuber chosen
    Stuber is a 2019 action-comedy film about a mild-mannered rideshare driver who gets roped into helping a tough cop track down a criminal, starring Kumail Nanjiani and Dave Bautista.
  • B. The Driver
    The Driver is the laconic, unnamed street racer portrayed by James Taylor in the 1971 cult road movie "Two-Lane Blacktop."
  • C. The Driver
    The Driver is a 1978 neo-noir crime thriller film written and directed by Walter Hill, centered on a taciturn, highly skilled getaway driver involved in a tense cat-and-mouse game with a relentless detective.
  • D. Cabbie
    Cabbie is a quirky, talkative New York City taxi driver who serves as a memorable supporting character in the dystopian action film "Escape from New York."
  • E. The Drive
    The Drive is a vibrant, culturally diverse neighborhood and commercial district in East Vancouver known for its eclectic shops, restaurants, and arts scene.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35958d49c8190b995188240fb355b completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee8812c81908ef74636bf39d44a completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.