Triple
T16079749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ostprignitz-Ruppin |
E390073
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Prignitz |
E983279
|
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: Prignitz | Statement: [Ostprignitz-Ruppin, borders, Prignitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prignitz Context triple: [Ostprignitz-Ruppin, borders, Prignitz]
-
A.
Prignitz
chosen
Prignitz is a rural district in northwestern Brandenburg, Germany, known for its historic towns, agricultural landscapes, and location along the Elbe River.
-
B.
Teltow
Teltow is a town in the German state of Brandenburg, located just southwest of Berlin and known for its historical core and proximity to the capital.
-
C.
Mecklenburg
Mecklenburg is a historical region in northern Germany, now part of the federal state of Mecklenburg-Vorpommern, known for its Baltic Sea coastline, lakes, and rural landscapes.
-
D.
Uckermark
Uckermark is a rural historical region in northeastern Germany, known for its lakes, forests, and low population density, located primarily in the state of Brandenburg.
-
E.
Ostprignitz-Ruppin
Ostprignitz-Ruppin is a rural district in the German state of Brandenburg, known for its lakes, forests, and historic towns such as Neuruppin.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18448bebc8190b0e84b1da097bf8b |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff798c2a48190b6eccd476a0a396f |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 4:57 a.m.