Triple

T85915
Position Surface form Disambiguated ID Type / Status
Subject Germany E1728 entity
Predicate hasAutomotiveIndustryBrand P4320 FINISHED
Object Audi E6000 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: Audi | Statement: [Germany, hasAutomotiveIndustryBrand, Audi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Audi
Context triple: [Germany, hasAutomotiveIndustryBrand, Audi]
  • A. Mercedes-Benz
    Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
  • B. BMW
    BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
  • C. Volkswagen Group chosen
    Volkswagen Group is a major German multinational automotive manufacturer that owns brands such as Volkswagen, Audi, Porsche, and Škoda and is one of the largest car producers in the world.
  • D. Saab Automobile
    Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
  • E. Stellantis
    Stellantis is a multinational automotive manufacturing corporation formed through the merger of Fiat Chrysler Automobiles and PSA Group, producing a wide range of vehicles under brands such as Jeep, Peugeot, Citroën, and Fiat.
  • 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_69a24c8150408190910a693eb51c1f71 completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a2567dd770819088eb77ffc6d2d1cf completed Feb. 28, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69a284fd52f08190b264937658192e79 completed Feb. 28, 2026, 6:02 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.