Triple
T23095814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribnitz-Damgarten |
E575883
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object | Ribnitz |
—
|
NE NERFINISHED |
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: Ribnitz | Statement: [Ribnitz-Damgarten, formedByMergerOf, Ribnitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ribnitz Context triple: [Ribnitz-Damgarten, formedByMergerOf, Ribnitz]
-
A.
Ribnitz-Damgarten
chosen
Ribnitz-Damgarten is a small town in northeastern Germany known as the “Bernsteinstadt” (Amber Town) for its long tradition of amber processing and its location near the Baltic Sea.
-
B.
Priestewitz
Priestewitz is a small municipality in the German state of Saxony that lies within the broader Leipzig metropolitan region.
-
C.
Löwenberg
Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
-
D.
Lüttkevitz
Lüttkevitz is a small village that forms part of the municipality of Dranske on the island of Rügen in Mecklenburg-Vorpommern, Germany.
-
E.
Leutenberg
Leutenberg is a small town in the German state of Thuringia, known for its location in the Thuringian Slate Mountains and its historical sites.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de522e48190a37e6c2fda2de465 |
completed | April 29, 2026, 4:49 a.m. |
Created at: April 17, 2026, 3:57 p.m.