Triple

T678822
Position Surface form Disambiguated ID Type / Status
Subject Buick E13135 entity
Predicate competitor P1375 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: [Buick, competitor, Volkswagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volkswagen
Context triple: [Buick, competitor, 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. Mercedes-Benz
    Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
  • E. Daimler AG
    Daimler AG was a major German multinational automotive corporation best known as the longtime manufacturer and corporate parent behind the Mercedes-Benz brand.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04e17088190943d54977eb3f83a completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a66d8f4a908190bc4cf5e1a6e46628 completed March 3, 2026, 5:11 a.m.
Created at: March 1, 2026, 7:36 p.m.