Triple

T13526863
Position Surface form Disambiguated ID Type / Status
Subject NIO E323034 entity
Predicate hasModel P2390 FINISHED
Object NIO ES6 E323034 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: NIO ES6 | Statement: [NIO, hasModel, NIO ES6]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NIO ES6
Context triple: [NIO, hasModel, NIO ES6]
  • A. NIO chosen
    NIO is a Chinese electric vehicle manufacturer known for its premium smart EVs and innovative battery-swapping technology.
  • B. N6
    N6 is a national route in South Africa that connects inland regions to the coastal city of East London, serving as a key north–south transport corridor.
  • C. NVE
    NVE is Norway’s national authority responsible for managing the country’s water and energy resources, including hydropower regulation, flood preparedness, and energy system oversight.
  • D. NOE
    NOE is the regional vehicle registration code used on car license plates issued in the town of Olecko in northeastern Poland.
  • E. NOE
    NOE (Nucleo Operativo Ecologico) is a specialized unit of the Italian Carabinieri focused on investigating and combating environmental crimes and protecting ecological resources.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafb8e0cc8190b47f6aeb8ced470e completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7549dda6481908e9305690488b1af completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:44 p.m.