Triple
T23458733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brühl, Germany |
E568006
|
entity |
| Predicate | distanceToCologne |
P152358
|
FINISHED |
| Object | approximately 12 kilometers |
—
|
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 12 kilometers | Statement: [Brühl, Germany, distanceToCologne, approximately 12 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCologne Context triple: [Brühl, Germany, distanceToCologne, approximately 12 kilometers]
-
A.
distanceToFrankfurt
Indicates the spatial distance between a given location or entity and the city of Frankfurt.
-
B.
distanceToDortmund
Indicates the spatial distance between a given entity’s location and the city of Dortmund.
-
C.
distanceToKoblenz
Indicates the spatial distance between a given entity and the location of Koblenz.
-
D.
distanceToWuppertal
Indicates the spatial distance between a given entity and the location of Wuppertal.
-
E.
distanceToWiesbaden
Indicates the spatial distance between a given entity or location and the city of Wiesbaden.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a699c0088190a84d7a495a3e3d61 |
completed | April 29, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69f06201d33481909b5fd7b92d03e658 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:53 p.m.