Triple
T9976730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juneyao Air |
E196348
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | 9 Air |
E185256
|
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: 9 Air | Statement: [Juneyao Air, hasSubsidiary, 9 Air]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 9 Air Context triple: [Juneyao Air, hasSubsidiary, 9 Air]
-
A.
9 Air
chosen
9 Air is a Chinese low-cost airline based in Guangzhou that operates domestic and regional passenger flights.
-
B.
AIR (SC)
AIR (SC) is a widely cited Indian law report series that publishes authoritative judgments of the Supreme Court of India.
-
C.
L’Air
L’Air is a celebrated early 20th-century sculpture by Aristide Maillol that exemplifies his serene, classical approach to the female form.
-
D.
Aero
Aero is a high-performance, sport-oriented trim level used by Saab for its 9-3 and other models, typically featuring more powerful engines and upgraded equipment.
-
E.
Air
Air is a French electronic music duo known for their atmospheric, downtempo sound and influential albums like "Moon Safari."
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84d0d3c8190b268582bb79c8973 |
completed | April 2, 2026, 12:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23de601f0819096004bf60ffa2d2c |
completed | April 5, 2026, 10:48 a.m. |
Created at: March 30, 2026, 8:48 p.m.