Triple

T13444963
Position Surface form Disambiguated ID Type / Status
Subject Lansing Delta Township Assembly E320456 entity
Predicate operator P179 FINISHED
Object General Motors 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: General Motors | Statement: [Lansing Delta Township Assembly, operator, General Motors]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: General Motors
Context triple: [Lansing Delta Township Assembly, operator, General Motors]
  • A. General Motors chosen
    General Motors is a major American multinational automotive manufacturer known for brands such as Chevrolet, GMC, Cadillac, and Buick.
  • B. Ford Motor Company
    Ford Motor Company is a major American automobile manufacturer, founded by Henry Ford, known for pioneering assembly-line mass production and producing iconic vehicles like the Model T and F-Series trucks.
  • C. Ford
    Ford is a small village in Argyll and Bute, western Scotland, known for its scenic location near Loch Awe and its historic rural character.
  • D. Ford
    Ford is a town in the Metropolitan Borough of Sefton, Merseyside, England, forming part of the northern suburbs of Liverpool.
  • E. Ford
    Ford is a small village in the Arun District of West Sussex, England, known for its rural character and nearby railway station.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaef5f610819092cad33ef72075ff completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7397f098c8190a2062d8c1a74d28f completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:40 p.m.