Triple

T1499708
Position Surface form Disambiguated ID Type / Status
Subject Mobileye E29767 entity
Predicate notableClient P7186 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: [Mobileye, notableClient, Audi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Audi
Context triple: [Mobileye, notableClient, 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. BMW
    BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6f0ce988190aafab4a6e0dfd710 completed March 1, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad2331b49881908672251bb86418df completed March 8, 2026, 7:20 a.m.
Created at: March 1, 2026, 8:12 p.m.