Triple
T3832533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Car of the Year |
E91045
|
entity |
| Predicate | notableWinner |
P2766
|
FINISHED |
| Object | Nissan Leaf |
E16980
|
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: Nissan Leaf | Statement: [European Car of the Year, notableWinner, Nissan Leaf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nissan Leaf Context triple: [European Car of the Year, notableWinner, Nissan Leaf]
-
A.
Nissan Leaf
chosen
The Nissan Leaf is a mass-market all-electric compact hatchback known for pioneering affordable zero-emission driving.
-
B.
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.
-
C.
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.
-
D.
Kia Niro EV
The Kia Niro EV is a compact all-electric crossover SUV known for its practical range, efficient performance, and versatile hatchback design.
-
E.
Ford Model e
Ford Model e is Ford Motor Company's dedicated division focused on developing and producing electric and connected 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8787bc8190819a7af975b609df |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503fcddb481909690b708754d3d8a |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:17 p.m.