Triple
T191287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Martí International Airport |
E3726
|
entity |
| Predicate | hasCustomsAndImmigration |
P7852
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [José Martí International Airport, hasCustomsAndImmigration, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomsAndImmigration Context triple: [José Martí International Airport, hasCustomsAndImmigration, yes]
-
A.
hasBorderCrossing
Indicates that there exists a point or facility where movement or transit is possible between the boundaries of two adjacent regions or jurisdictions.
-
B.
customsRegime
Indicates the specific customs treatment or regulatory framework under which goods are imported, exported, or stored.
-
C.
placeOfArrival
Indicates the location at which an entity or person arrives at the end of a journey, movement, or transfer.
-
D.
hasCargoTerminal
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
E.
hasHomeland
Indicates that an entity considers or recognizes a particular place or region as its homeland or place of origin.
- 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_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. |
| PDg | Predicate description generation | batch_69a258fbd18881908c9d40f7a2480945 |
completed | Feb. 28, 2026, 2:54 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.