Triple
T14517732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangalore International Airport Limited |
E340566
|
entity |
| Predicate | operatedAirportType |
P98427
|
FINISHED |
| Object | international airport |
—
|
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: international airport | Statement: [Bangalore International Airport Limited, operatedAirportType, international airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedAirportType Context triple: [Bangalore International Airport Limited, operatedAirportType, international airport]
-
A.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
B.
operatesAirport
Indicates that one entity manages and runs the operations of an airport.
-
C.
servesAirportType
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
-
D.
airportTypeManaged
chosen
Indicates that an entity is responsible for managing or overseeing a particular type or category of airport.
-
E.
aircraftOperationType
Indicates the specific manner or purpose for which an aircraft is being operated (e.g., commercial, private, military, training).
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a6f50208190b687b505f5cd1aa2 |
completed | April 14, 2026, 7:50 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:22 a.m.