Triple
T20849543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buxtehude |
E513318
|
entity |
| Predicate | partOfRegion |
P285
|
FINISHED |
| Object | Altes Land |
—
|
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: Altes Land | Statement: [Buxtehude, partOfRegion, Altes Land]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altes Land Context triple: [Buxtehude, partOfRegion, Altes Land]
-
A.
Land of Hadeln
chosen
The Land of Hadeln is a historic coastal region in northern Germany, known for its fertile marshlands, dike systems, and long-standing agricultural traditions along the lower Elbe.
-
B.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
C.
Orlamünde
Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
-
D.
Wartheland
Wartheland was a Nazi German-occupied region of western Poland during World War II, notorious for its role in the Holocaust and the implementation of genocidal policies against Jews and other targeted groups.
-
E.
Löwenberger Land
Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3520b0081908ce0f43e8f20b24c |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.