Triple

T3737844
Position Surface form Disambiguated ID Type / Status
Subject Holden Calais E79627 entity
Predicate manufacturer P490 FINISHED
Object Holden E2747 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: Holden | Statement: [Holden Calais, manufacturer, Holden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holden
Context triple: [Holden Calais, manufacturer, Holden]
  • A. Holden chosen
    Holden was an Australian automobile manufacturer and marque owned by General Motors, known for producing popular locally designed cars before ceasing operations in the 21st century.
  • B. Holden
    Holden is a suburban town in Worcester County, Massachusetts, known for its residential character and proximity to the city of Worcester.
  • C. Holden
    Holden is a small town in central Utah, United States, known for its rural character and proximity to Interstate 15.
  • D. Doc Hudson
    Doc Hudson is a wise, retired race car and town doctor in Pixar's "Cars" who mentors the protagonist Lightning McQueen.
  • E. Dana Brown
    Dana Brown is a Major League Baseball executive best known as the general manager of the Houston Astros, overseeing the club’s player personnel and roster decisions.
  • 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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb3e9248819098d481fe29e1c628 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f02aac60819095e62cc5e792d538 completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:34 p.m.