Triple
T201561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baojun |
E4516
|
entity |
| Predicate | hasModel |
P2390
|
FINISHED |
| Object | Baojun 510 |
E4516
|
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: Baojun 510 | Statement: [Baojun, hasModel, Baojun 510]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baojun 510 Context triple: [Baojun, hasModel, Baojun 510]
-
A.
Baojun
chosen
Baojun is a Chinese automobile marque known for producing affordable mass-market vehicles through a joint venture involving General Motors.
-
B.
Wuling
Wuling is a Chinese automotive marque known for producing affordable compact cars and microvans, marketed through a joint venture involving General Motors.
-
C.
SAIC Motor
SAIC Motor is a major Chinese state-owned automotive manufacturer and one of the country’s largest carmakers, producing vehicles under its own brands and through joint ventures with global and regional partners.
-
D.
Hyundai Kona Electric
The Hyundai Kona Electric is a subcompact all-electric crossover SUV known for its practical range, compact size, and affordability in the mainstream EV market.
-
E.
Nissan Leaf
The Nissan Leaf is a mass-market all-electric compact hatchback known for pioneering affordable zero-emission driving.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25be5a6d081909723b23a6361d6ea |
completed | Feb. 28, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a32813ed0c8190bebd5129eb5ebfe7 |
completed | Feb. 28, 2026, 5:38 p.m. |
Created at: Feb. 28, 2026, 2:51 a.m.