Triple
T15687354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnim |
E380235
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Werneuchen |
E326287
|
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: Werneuchen | Statement: [Barnim, hasMunicipality, Werneuchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werneuchen Context triple: [Barnim, hasMunicipality, Werneuchen]
-
A.
Werneuchen
chosen
Werneuchen is a small town in the German state of Brandenburg, located northeast of Berlin and characterized by its rural surroundings and commuter links to the capital.
-
B.
Wustermark
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
-
C.
Weidenau
Weidenau is a district of the city of Siegen in North Rhine-Westphalia, Germany.
-
D.
Heuckewalde
Heuckewalde is a small municipality in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan region.
-
E.
Wernborn
Wernborn is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4cee5481908699fbb2b7bdd2f6 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0025e9b00c81908cb5f305c894363f |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 4:44 a.m.