Triple
T28225176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cologne Bonn Airport |
E711565
|
entity |
| Predicate | distanceToBonnCentre |
P201094
|
FINISHED |
| Object | approximately 16 km northeast |
—
|
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 16 km northeast | Statement: [Cologne Bonn Airport, distanceToBonnCentre, approximately 16 km northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBonnCentre Context triple: [Cologne Bonn Airport, distanceToBonnCentre, approximately 16 km northeast]
-
A.
distanceToKoblenz
Indicates the spatial distance between a given entity and the location of Koblenz.
-
B.
distanceFromHagenHbf_km
Indicates the distance, measured in kilometers, between a given location and Hagen Hauptbahnhof (Hagen central railway station).
-
C.
distanceFromDarmstadtHbf
Indicates the spatial distance between a given location and Darmstadt Hauptbahnhof (Darmstadt central railway station).
-
D.
distanceToWuppertal
Indicates the spatial distance between a given entity and the location of Wuppertal.
-
E.
distanceToBordeauxCenter
Indicates the measured or calculated distance between a given entity’s location and the center of Bordeaux.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ffc7b4c7f88190b6357a44e7f0940f |
completed | May 9, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69ffc755f09c8190995ca00d97336988 |
completed | May 9, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69ffc7b41e688190ad3b86d87c38888e |
completed | May 9, 2026, 11:48 p.m. |
Created at: April 27, 2026, 10:49 p.m.