Triple

T633858
Position Surface form Disambiguated ID Type / Status
Subject National Electric Vehicle Sweden E15978 entity
Predicate abbreviation P43 FINISHED
Object NEVS E79648 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: NEVS | Statement: [National Electric Vehicle Sweden, abbreviation, NEVS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NEVS
Context triple: [National Electric Vehicle Sweden, abbreviation, NEVS]
  • A. NEVS chosen
    NEVS is a Swedish electric vehicle manufacturer that emerged from the acquisition of Saab Automobile’s assets, focusing on sustainable mobility solutions.
  • B. de Neve
    De Neve is a Spanish surname historically associated with notable figures such as colonial administrators and military officers in Spain and its former territories.
  • C. Ford Model e
    Ford Model e is Ford Motor Company's dedicated division focused on developing and producing electric and connected vehicles.
  • D. 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.
  • E. Nye
    Nye is the surname of Bill Nye, the American science educator, mechanical engineer, and television presenter widely known as "Bill Nye the Science Guy."
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ec3b6488190aa0dce216c089a2e completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5778b82e8819083fbbedb9c3e340e completed March 2, 2026, 11:42 a.m.
Created at: March 1, 2026, 7:35 p.m.