Triple
T11145311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 4 (Ninoy Aquino International Airport) |
E263653
|
entity |
| Predicate | hasNumberOfPassengerTerminalsAtAirport |
P98033
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Terminal 4 (Ninoy Aquino International Airport), hasNumberOfPassengerTerminalsAtAirport, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPassengerTerminalsAtAirport Context triple: [Terminal 4 (Ninoy Aquino International Airport), hasNumberOfPassengerTerminalsAtAirport, 4]
-
A.
airportHasTerminals
Indicates that a particular airport includes or is composed of one or more terminal facilities.
-
B.
hasPassengerTerminalFacilities
Indicates that an entity provides facilities or infrastructure specifically intended for handling and serving passengers.
-
C.
hasPassengerBoardingGates
Indicates that an entity is associated with or contains one or more passenger boarding gates used for embarking or disembarking passengers.
-
D.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
E.
isPassengerAirport
Indicates that an airport primarily serves commercial passenger air traffic rather than cargo or other specialized operations.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8634d5481909b114d30a542ea3f |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:28 p.m.