Triple
T29434290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noida International Airport |
E746523
|
entity |
| Predicate | plannedPassengerCapacityUltimatePerYear |
P12993
|
FINISHED |
| Object | 70 million passengers |
—
|
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: 70 million passengers | Statement: [Noida International Airport, plannedPassengerCapacityUltimatePerYear, 70 million passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedPassengerCapacityUltimatePerYear Context triple: [Noida International Airport, plannedPassengerCapacityUltimatePerYear, 70 million passengers]
-
A.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
B.
hasAnnualPassengerTrafficOver
Indicates that the subject location or transport facility experiences an annual passenger volume exceeding a specified threshold.
-
C.
hasNumberOfSeatsAtPeak
Indicates the maximum number of seats available or occupied at the peak usage or capacity of something.
-
D.
annualCapacity
chosen
Indicates the maximum amount of output or throughput an entity can produce or handle within a one-year period.
-
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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 28, 2026, 3:15 p.m.