Triple
T20838139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Appenweier |
E513015
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Willstätt |
—
|
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: Willstätt | Statement: [Appenweier, hasNeighbouringMunicipality, Willstätt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willstätt Context triple: [Appenweier, hasNeighbouringMunicipality, Willstätt]
-
A.
Willstätt
chosen
Willstätt is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine and the French border.
-
B.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
C.
Weinstadt
Weinstadt is a town in the German state of Baden-Württemberg, known for its winegrowing tradition in the Rems Valley near Stuttgart.
-
D.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
E.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
- 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_69e0b4cf62a88190bbf92351e9e57259 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c32928788190be8ca57923eefd7e |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:42 p.m.