Triple
T7686242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melgar |
E174122
|
entity |
| Predicate | travelTimeFromBogotáByCar |
P78708
|
FINISHED |
| Object | approximately 2–3 hours |
—
|
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 2–3 hours | Statement: [Melgar, travelTimeFromBogotáByCar, approximately 2–3 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeFromBogotáByCar Context triple: [Melgar, travelTimeFromBogotáByCar, approximately 2–3 hours]
-
A.
distanceFromBogotá
Indicates the spatial distance separating a given entity or location from the city of Bogotá.
-
B.
directionFromBogotá
Indicates the cardinal or relative compass direction in which one place or object lies when measured from Bogotá.
-
C.
distanceToSantaMarta
Indicates the measured spatial distance between a given entity’s location and the location of Santa Marta.
-
D.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
E.
drivingTimeFromNewYorkCity
Indicates the amount of time it takes to drive from New York City to a specified location.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c706d0c1708190a3e74523997814b8 |
completed | March 27, 2026, 10:38 p.m. |
Created at: March 27, 2026, 4:02 p.m.