Triple
T33696089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MDE |
E863315
|
entity |
| Predicate | associatedAirportDistanceFromCityCentre |
P79745
|
FINISHED |
| Object | about 20 kilometres southeast of Medellín |
—
|
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: about 20 kilometres southeast of Medellín | Statement: [MDE, associatedAirportDistanceFromCityCentre, about 20 kilometres southeast of Medellín]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportDistanceFromCityCentre Context triple: [MDE, associatedAirportDistanceFromCityCentre, about 20 kilometres southeast of Medellín]
-
A.
distanceToAirport
chosen
Indicates the measured distance between a given location and the nearest or specified airport.
-
B.
distanceToMBBAirport_km
Indicates the distance, measured in kilometers, from a given location to the MBB airport.
-
C.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
-
D.
distanceToFrankfurtAirport_km
Indicates the physical distance, measured in kilometers, between a given location and Frankfurt Airport.
-
E.
nearbyAirportRelationship
Indicates that one location has an airport situated close enough to serve it conveniently, establishing a nearby-airport relationship between the two.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:43 a.m.