Triple

T1762889
Position Surface form Disambiguated ID Type / Status
Subject Cariad E38696 entity
Predicate servesBrand P6337 FINISHED
Object Volkswagen 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: Volkswagen | Statement: [Cariad, servesBrand, Volkswagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volkswagen
Context triple: [Cariad, servesBrand, Volkswagen]
  • A. 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.
  • B. Audi
    Audi is a German luxury automobile manufacturer known for its premium vehicles, advanced engineering, and signature quattro all-wheel-drive technology.
  • C. Porsche
    Porsche is a German luxury automobile manufacturer renowned for its high-performance sports cars, SUVs, and engineering excellence.
  • D. Volkswagen Truck & Bus
    Volkswagen Truck & Bus is a commercial vehicle manufacturer within the Volkswagen Group, known for producing trucks and buses for global markets.
  • E. Volkswagen Commercial Vehicles
    Volkswagen Commercial Vehicles is a division of the Volkswagen Group specializing in the development, production, and sale of light commercial vehicles such as vans and pickups for business and private use.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6465245c8190b1ee84628c62c529 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fc02b948190bc28175ff8c46110 completed March 9, 2026, 1:17 a.m.
Created at: March 4, 2026, 7:31 p.m.