Triple
T35907836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palmerola International Airport |
E1038518
|
entity |
| Predicate | distanceFromTegucigalpaKilometers |
P70017
|
FINISHED |
| Object | approximately 80 |
—
|
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: approximately 80 | Statement: [Palmerola International Airport, distanceFromTegucigalpaKilometers, approximately 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTegucigalpaKilometers Context triple: [Palmerola International Airport, distanceFromTegucigalpaKilometers, approximately 80]
-
A.
distanceFromTegucigalpa
chosen
Indicates the spatial distance between a given location and the city of Tegucigalpa.
-
B.
distanceToSanPedroSula
Indicates the spatial distance between a given entity and the location of San Pedro Sula.
-
C.
distanceFromManagua
Indicates the spatial distance between a given entity and the location of Managua.
-
D.
distanceFromSanSalvador
Indicates the measured distance between an entity and the location of San Salvador.
-
E.
distanceFromBelizeCity
Indicates the spatial distance separating a given place or object from Belize City.
- 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.