Triple

T20246061
Position Surface form Disambiguated ID Type / Status
Subject 2006 Paris Motor Show E498426 entity
Predicate hasExhibitor P33707 FINISHED
Object Ford NE NERFINISHED

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: Ford | Statement: [2006 Paris Motor Show, hasExhibitor, Ford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ford
Context triple: [2006 Paris Motor Show, hasExhibitor, Ford]
  • A. Ford
    Ford is a common English surname borne by numerous notable individuals, including U.S. President Gerald Ford.
  • B. Ford
    Ford is a town in the Metropolitan Borough of Sefton, Merseyside, England, forming part of the northern suburbs of Liverpool.
  • C. Ford
    Ford is a small village in the Arun District of West Sussex, England, known for its rural character and nearby railway station.
  • D. 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.
  • E. Ford Motor Company chosen
    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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a26c8481908f408fb6426aece9 completed April 20, 2026, 6:42 p.m.
Created at: April 11, 2026, 11:40 p.m.