Triple

T4978013
Position Surface form Disambiguated ID Type / Status
Subject Tesla app E111815 entity
Predicate supportsProduct P18380 FINISHED
Object Tesla Model 3 E8414 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: Tesla Model 3 | Statement: [Tesla app, supportsProduct, Tesla Model 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tesla Model 3
Context triple: [Tesla app, supportsProduct, Tesla Model 3]
  • A. Tesla Model 3 chosen
    The Tesla Model 3 is a mass-market electric sedan known for its long range, high performance, and role in popularizing electric vehicles worldwide.
  • B. Tesla Model S
    The Tesla Model S is a luxury all-electric sedan known for its long range, high performance, and role in popularizing mainstream electric vehicles.
  • C. Tesla Model Y
    The Tesla Model Y is a compact all-electric crossover SUV known for its long range, advanced driver-assistance features, and minimalist high-tech interior.
  • D. BYD Atto 3
    The BYD Atto 3 is a compact electric SUV from Chinese automaker BYD, known for its competitive range, affordability, and use of BYD’s Blade Battery technology.
  • E. Volkswagen ID.3
    The Volkswagen ID.3 is a compact all-electric hatchback from Volkswagen’s ID family, designed as a mass-market EV successor to the Golf in Europe.
  • 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_69bd441adc208190b70a033a0741d01e completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7232bd8c8190b325c9198e8b2fa1 completed March 20, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a0ac8d48190b9d050e26b67a794 completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:33 p.m.