Triple
T18046147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheingau-Taunus-Kreis |
E431777
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Oestrich-Winkel |
—
|
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: Oestrich-Winkel | Statement: [Rheingau-Taunus-Kreis, containsTown, Oestrich-Winkel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oestrich-Winkel Context triple: [Rheingau-Taunus-Kreis, containsTown, Oestrich-Winkel]
-
A.
Oestrich-Winkel
chosen
Oestrich-Winkel is a historic wine-growing town in Germany’s Rheingau region, renowned for its Riesling vineyards along the Rhine River.
-
B.
Badenweiler
Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
-
C.
Gerlachsheim
Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
-
D.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
E.
Vaihingen
Vaihingen is a district in the southwest of Stuttgart, Germany, known for its mix of residential areas, business parks, and proximity to major transport links.
- 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.