Triple
T17064286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Büchel Air Base |
E414041
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Cochem |
E336098
|
NE 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: Cochem | Statement: [Büchel Air Base, near, Cochem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cochem Context triple: [Büchel Air Base, near, Cochem]
-
A.
Cochem
chosen
Cochem is a picturesque German town in the Rhineland-Palatinate region, renowned for its hilltop Reichsburg Castle, half-timbered houses, and scenic vineyards along the Moselle Valley.
-
B.
Berchem
Berchem is a district of the Belgian city of Antwerp, known for its residential neighborhoods, Art Nouveau architecture, and vibrant local culture.
-
C.
Chamerbach
Chamerbach is a small river in central Switzerland that serves as one of the tributaries feeding into Lake Zug.
-
D.
Cherain
Cherain is a small village in the municipality of Gouvy in the province of Luxembourg, Belgium.
-
E.
Boechout
Boechout is a municipality in the Belgian province of Antwerp, known for its suburban character and proximity to the city of Antwerp.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7f6a6081909bebce3ce925e663 |
completed | April 18, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01234e9a94819094618ba43b7d22b4 |
completed | May 11, 2026, 12:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.