Triple

T25346
Position Surface form Disambiguated ID Type / Status
Subject General Motors E506 entity
Predicate brand P1500 FINISHED
Object Buick E506 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: Buick | Statement: [General Motors, brand, Buick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buick
Context triple: [General Motors, brand, Buick]
  • A. Chevrolet
    Chevrolet is a major American automobile marque known for producing a wide range of affordable cars, trucks, and SUVs.
  • B. General Motors chosen
    General Motors is a major American multinational automotive manufacturer known for brands such as Chevrolet, GMC, Cadillac, and Buick.
  • C. Packard
    Packard is a surname most prominently associated with David Packard, the American electrical engineer and co-founder of Hewlett-Packard.
  • D. Oldsmobile Delmont 88
    The Oldsmobile Delmont 88 is a full-size American car produced by Oldsmobile in the late 1960s, known historically for being the model involved in the Chappaquiddick incident.
  • E. Hummer
    Hummer is a line of large, military-inspired sport utility vehicles known for their rugged off-road capability, boxy design, and high fuel consumption.
  • 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_69a243b4ac2c8190b93c303df797b7b2 completed Feb. 28, 2026, 1:24 a.m.
NER Named-entity recognition batch_69a2481f9eac819093d9a950eb1ab109 completed Feb. 28, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2623969188190814f662922953e39 completed Feb. 28, 2026, 3:34 a.m.
Created at: Feb. 28, 2026, 1:34 a.m.