Triple
T18046149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheingau-Taunus-Kreis |
E431777
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Geisenheim |
—
|
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: Geisenheim | Statement: [Rheingau-Taunus-Kreis, containsTown, Geisenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geisenheim Context triple: [Rheingau-Taunus-Kreis, containsTown, Geisenheim]
-
A.
Geisenheim
chosen
Geisenheim is a German town in the Rheingau wine region, known for its viticulture, wine production, and renowned university of applied sciences for wine and horticulture.
-
B.
Passenheim
Passenheim is the former German name of the town now known as Pasym, located in northeastern Poland’s historic region of Masuria.
-
C.
Ottmarsheim
Ottmarsheim is a commune in northeastern France’s Alsace region, known for its historic Romanesque church and location along the Rhine.
-
D.
Wiehl
Wiehl is a small town in western Germany’s North Rhine-Westphalia region, known for its picturesque setting in the hilly Bergisches Land and its mix of rural charm and light industry.
-
E.
Wiehl
Wiehl is a river in North Rhine-Westphalia, Germany, that flows through the Bergisches Land region before joining the Agger.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff202088190ae971879348e2294 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 10:25 a.m.