Triple
T36240943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Thanh International Airport |
E891514
|
entity |
| Predicate | plannedUltimateCapacityPassengersPerYear |
P12993
|
FINISHED |
| Object | 100 million |
—
|
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: 100 million | Statement: [Long Thanh International Airport, plannedUltimateCapacityPassengersPerYear, 100 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedUltimateCapacityPassengersPerYear Context triple: [Long Thanh International Airport, plannedUltimateCapacityPassengersPerYear, 100 million]
-
A.
hasAnnualPassengerTrafficOver
Indicates that the subject location or transport facility experiences an annual passenger volume exceeding a specified threshold.
-
B.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
C.
annualCapacity
chosen
Indicates the maximum amount of output or throughput an entity can produce or handle within a one-year period.
-
D.
hasApproximateAnnualCargoThroughput
Indicates that an entity is associated with an estimated or approximate amount of cargo it handles over the course of a year.
-
E.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
- 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_69f76e44993481908fa75e4c48d0aab3 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
Created at: May 3, 2026, 4:09 p.m.