Triple

T7731258
Position Surface form Disambiguated ID Type / Status
Subject Franz von Holzhausen E175260 entity
Predicate designed P184 FINISHED
Object Tesla Cybertruck E10796 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 Cybertruck | Statement: [Franz von Holzhausen, designed, Tesla Cybertruck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tesla Cybertruck
Context triple: [Franz von Holzhausen, designed, Tesla Cybertruck]
  • A. Tesla Cybertruck chosen
    The Tesla Cybertruck is an all-electric, angularly styled pickup truck known for its stainless-steel exoskeleton, high performance, and futuristic design.
  • B. Tesla Vision
    Tesla Vision is Tesla’s camera-based driver-assistance and autonomous driving system that relies solely on vision processing instead of radar or lidar sensors.
  • C. Tesla Semi
    The Tesla Semi is an all-electric Class 8 semi-truck designed to offer high efficiency, long range, and lower operating costs compared to traditional diesel trucks.
  • D. Tesla Roadster
    The Tesla Roadster is an all-electric sports car that marked Tesla’s debut in the automotive market and helped popularize high-performance electric vehicles.
  • E. 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.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70336aafc819099a060950ab8922f completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b52e176481908595fea4ace7a607 completed March 29, 2026, 5:14 a.m.
Created at: March 27, 2026, 4:06 p.m.