Triple
T26814209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuluá |
E672079
|
entity |
| Predicate | roadDistanceToBogotá |
P29005
|
FINISHED |
| Object | several hundred kilometers southwest of Bogotá |
—
|
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: several hundred kilometers southwest of Bogotá | Statement: [Tuluá, roadDistanceToBogotá, several hundred kilometers southwest of Bogotá]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToBogotá Context triple: [Tuluá, roadDistanceToBogotá, several hundred kilometers southwest of Bogotá]
-
A.
distanceFromBogotá
chosen
Indicates the spatial distance separating a given entity or location from the city of Bogotá.
-
B.
travelTimeFromBogotáByCar
Indicates the amount of time it takes to travel by car from Bogotá to a specified destination.
-
C.
directionFromBogotá
Indicates the cardinal or relative compass direction in which one place or object lies when measured from Bogotá.
-
D.
distanceFromMedellín
Indicates the measured spatial distance between an entity and the city of Medellín.
-
E.
distanceToSantaMarta
Indicates the measured spatial distance between a given entity’s location and the location of Santa Marta.
- 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_69eeb3225a3c8190aaf6746efeded2f3 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f61a83c8ec8190ba1f49371889e547 |
completed | May 2, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:31 a.m.