Triple

T4529843
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen ID.3 E106266 entity
Predicate intendedCompetitors P1375 FINISHED
Object Renault Zoe E446414 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: Renault Zoe | Statement: [Volkswagen ID.3, intendedCompetitors, Renault Zoe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Renault Zoe
Context triple: [Volkswagen ID.3, intendedCompetitors, Renault Zoe]
  • A. Renault Zoe chosen
    The Renault Zoe is a compact all-electric hatchback known for popularizing affordable urban electric mobility in Europe.
  • B. Nissan Leaf
    The Nissan Leaf is a mass-market all-electric compact hatchback known for pioneering affordable zero-emission driving.
  • C. BMW i3
    The BMW i3 is a compact, all-electric city car known for its distinctive design, lightweight carbon-fiber construction, and focus on sustainable urban mobility.
  • D. Mitsubishi i-MiEV
    The Mitsubishi i-MiEV is a compact all-electric city car from Mitsubishi Motors, recognized as one of the early mass-produced electric vehicles.
  • E. Chevrolet Bolt EV
    The Chevrolet Bolt EV is a compact all-electric hatchback known for its relatively long driving range, affordability, and role in popularizing mainstream electric vehicles in North America.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6231856c8190be9386a0ae15e7cf completed March 20, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda46101648190b0c3ca8cfe54b965 completed March 20, 2026, 7:47 p.m.
Created at: March 20, 2026, 1:03 p.m.