Triple
T20826202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kippenheim |
E512705
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Kippenheim (village) |
—
|
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: Kippenheim (village) | Statement: [Kippenheim, hasSubdivision, Kippenheim (village)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kippenheim (village) Context triple: [Kippenheim, hasSubdivision, Kippenheim (village)]
-
A.
Kuppenheim
Kuppenheim is a small town in the Rastatt district of Baden-Württemberg, southwestern Germany, situated near the Black Forest.
-
B.
Kippenheim
chosen
Kippenheim is a municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine and the French border.
-
C.
Oberickelsheim
Oberickelsheim is a small rural municipality in the district of Neustadt an der Aisch-Bad Windsheim in the German state of Bavaria.
-
D.
Schweinheim
Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
-
E.
Martinsheim
Martinsheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian landscape.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2fd8480819099930af691d97477 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.