Triple

T514274
Position Surface form Disambiguated ID Type / Status
Subject BMW E10671 entity
Predicate competitor P1375 FINISHED
Object Mercedes-Benz E11202 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: Mercedes-Benz | Statement: [BMW, competitor, Mercedes-Benz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mercedes-Benz
Context triple: [BMW, competitor, Mercedes-Benz]
  • A. Mercedes-Benz chosen
    Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
  • B. Porsche
    Porsche is a German luxury automobile manufacturer renowned for its high-performance sports cars, SUVs, and engineering excellence.
  • C. Audi
    Audi is a German luxury automobile manufacturer known for its premium vehicles, advanced engineering, and signature quattro all-wheel-drive technology.
  • D. Bentley
    Bentley is a British luxury automobile manufacturer renowned for its high-performance grand tourers and handcrafted interiors.
  • E. Volkswagen Group
    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.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1824a248190808591ab3ece7dff completed Feb. 28, 2026, 1:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ab1bc2e48190b15d777af2a76a1a completed March 1, 2026, 9:09 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.