Triple
T30481362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riyadh Air |
E775595
|
entity |
| Predicate | targetPassengersBy2030 |
P882
|
FINISHED |
| Object | over 100 destinations |
—
|
LITERAL 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: over 100 destinations | Statement: [Riyadh Air, targetPassengersBy2030, over 100 destinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetPassengersBy2030 Context triple: [Riyadh Air, targetPassengersBy2030, over 100 destinations]
-
A.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
B.
passengersCountApproximate
chosen
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
C.
envisionedPopulation
Indicates a relationship where an entity specifies or projects an expected or target population size for something (such as a place, project, or scenario).
-
D.
servedPassengerTraffic
Indicates that an entity has provided transportation services to a certain volume or set of passengers.
-
E.
yearTransported
Indicates the specific year in which an entity was transported from one place to another.
- F. None of above.
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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd474b7e788190a9bb9b542d878f60 |
completed | May 8, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69fd46d8b2f0819099d92d72c902f60e |
completed | May 8, 2026, 2:13 a.m. |
Created at: April 29, 2026, 8:12 p.m.