Triple
T191286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Martí International Airport |
E3726
|
entity |
| Predicate | namedForOccupationOfEponym |
P365
|
FINISHED |
| Object | Cuban national hero and writer |
—
|
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: Cuban national hero and writer | Statement: [José Martí International Airport, namedForOccupationOfEponym, Cuban national hero and writer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForOccupationOfEponym Context triple: [José Martí International Airport, namedForOccupationOfEponym, Cuban national hero and writer]
-
A.
namesakeOccupation
chosen
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
-
B.
notableScientist
Indicates that the subject is a scientist who is widely recognized for significant contributions or impact in their field.
-
C.
notableCulturalFigure
Indicates that a person holds significant influence or recognition within a culture’s arts, traditions, values, or public life.
-
D.
pioneerOf
Indicates that an entity was among the first to develop, introduce, or significantly advance another entity, concept, or practice.
-
E.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
- 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.