Triple
T685835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Daxing International Airport |
E13280
|
entity |
| Predicate | designedCargoCapacity |
P18218
|
FINISHED |
| Object | 2 million tonnes per year |
—
|
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: 2 million tonnes per year | Statement: [Beijing Daxing International Airport, designedCargoCapacity, 2 million tonnes per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedCargoCapacity Context triple: [Beijing Daxing International Airport, designedCargoCapacity, 2 million tonnes per year]
-
A.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
B.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
C.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
-
D.
cargoHoldWidth
Indicates the width dimension of a cargo hold in a vehicle, vessel, or storage structure.
-
E.
cargoCapacityFromISS
Indicates the amount of cargo capacity that is transported from the International Space Station to another location or vehicle.
- F. None of above. chosen
Provenance (4 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d2048d48190ab99ab59accb6909 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a4a0f405748190ba72a9cfe946a8ec |
completed | March 1, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:36 p.m.