Triple

T8740188
Position Surface form Disambiguated ID Type / Status
Subject Louisville Assembly Plant E207479 entity
Predicate product P490 FINISHED
Object Ford vehicles E750075 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: Ford vehicles | Statement: [Louisville Assembly Plant, product, Ford vehicles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ford vehicles
Context triple: [Louisville Assembly Plant, product, Ford vehicles]
  • A. Ford vehicles chosen
    Ford vehicles are a range of automobiles produced by the Ford Motor Company, including cars, trucks, SUVs, and commercial vehicles sold worldwide.
  • B. Toyota vehicles
    Toyota vehicles are a globally recognized line of reliable, fuel-efficient cars, trucks, and SUVs produced by the Japanese automaker Toyota.
  • C. Ford platforms
    Ford platforms are the underlying vehicle architectures developed by the Ford Motor Company to support multiple models sharing common structural and mechanical components.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d486e34819094a6c6ec26c047cf completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42e7176c819097e313ed8e8ceb06 completed April 3, 2026, 4:32 a.m.
Created at: March 30, 2026, 6:38 p.m.