Triple
T191273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Martí International Airport |
E3726
|
entity |
| Predicate | primaryInternationalTerminal |
P1297
|
FINISHED |
| Object | Terminal 3 |
—
|
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: Terminal 3 | Statement: [José Martí International Airport, primaryInternationalTerminal, Terminal 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryInternationalTerminal Context triple: [José Martí International Airport, primaryInternationalTerminal, Terminal 3]
-
A.
hasInternationalAirport
Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
-
B.
primaryHubFor
Indicates that one entity serves as the main central hub or core point of coordination for another entity or set of entities.
-
C.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
D.
hasPassengerTerminal
chosen
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
E.
isInternational
Indicates that something has a connection to, involves, or extends across more than one country.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25964fc5c8190bd3e37daaf695ecf |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.