Triple

T9986864
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Group vehicle engineering divisions E196790 entity
Predicate supportsBrand P91438 FINISHED
Object Audi E37745 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: [Volkswagen Group vehicle engineering divisions, supportsBrand, Audi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Audi
Context triple: [Volkswagen Group vehicle engineering divisions, supportsBrand, Audi]
  • A. Audi chosen
    Audi is a German luxury automobile manufacturer known for its premium vehicles, advanced engineering, and signature quattro all-wheel-drive technology.
  • B. Porsche
    Porsche is a German luxury automobile manufacturer renowned for its high-performance sports cars, SUVs, and engineering excellence.
  • C. Mercedes-Benz
    Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
  • D. Audi Q series
    The Audi Q series is a lineup of luxury SUV and crossover models produced by Audi, known for combining premium interiors, advanced technology, and all-wheel-drive performance.
  • E. BMW
    BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
  • 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_69ca82f1678c819093d06320a05f16a4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdc79c8b80819091dc16ac8fd0c720 completed April 2, 2026, 1:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6527343048190b3bb13b33c32fbf7 completed April 8, 2026, 1:04 p.m.
Created at: March 30, 2026, 8:50 p.m.