Triple
T5355761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baumwerder |
E102686
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Baumwerder (German) |
E102686
|
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: Baumwerder (German) | Statement: [Baumwerder, hasNameInLanguage, Baumwerder (German)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baumwerder (German) Context triple: [Baumwerder, hasNameInLanguage, Baumwerder (German)]
-
A.
Baumwerder
chosen
Baumwerder is a small island located in Tegeler See, a lake in the Berlin district of Reinickendorf, Germany.
-
B.
Bramsche
Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
-
C.
Französisch Buchholz
Französisch Buchholz is a northeastern locality of Berlin known for its village-like character and incorporation into the borough of Pankow.
-
D.
Braunlage
Braunlage is a German town and ski resort in the Harz Mountains, known for its winter sports, hiking opportunities, and scenic natural surroundings.
-
E.
Oberkrämer
Oberkrämer is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its villages, agricultural landscape, and proximity to Berlin.
- 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_69bd43d8f7248190b64c140734b5c9a8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd862f0ea48190bec78690ab3bee51 |
completed | March 20, 2026, 5:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21e2b7b08190aca4c2855ff041de |
completed | March 21, 2026, 10:55 p.m. |
Created at: March 20, 2026, 2:01 p.m.