Triple
T22789332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallenberg |
E564064
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Bromskirchen |
E1059434
|
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: Bromskirchen | Statement: [Hallenberg, locatedNear, Bromskirchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bromskirchen Context triple: [Hallenberg, locatedNear, Bromskirchen]
-
A.
Bromskirchen
chosen
Bromskirchen is a small municipality in the Waldeck-Frankenberg district of Hesse, Germany, near the border with North Rhine-Westphalia.
-
B.
Kaldenkirchen
Kaldenkirchen is a town in western Germany near the Dutch border, known as a key cross-border transport point with direct access to major motorway routes.
-
C.
Sulzheim
Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
D.
Iffezheim
Iffezheim is a municipality in southwestern Germany best known for its major horse racing track, one of the most important in the country.
-
E.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c3488708190812f7d2edac92184 |
completed | April 29, 2026, 3:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bf28f11c481908d5e464f31aeada3 |
completed | May 19, 2026, 5:18 a.m. |
Created at: April 17, 2026, 3:29 p.m.