Triple
T18325820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dagstuhl |
E439003
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Wadern |
—
|
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: Wadern | Statement: [Dagstuhl, hasMunicipality, Wadern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wadern Context triple: [Dagstuhl, hasMunicipality, Wadern]
-
A.
Wadern
chosen
Wadern is a small town in the Saarland region of western Germany, known for its rural character and location near the borders with Luxembourg and France.
-
B.
Wern
The Wern is a river in northern Bavaria, Germany, that flows through the Schweinfurt region before joining the Main River.
-
C.
Wangen
Wangen is a locality in the Swiss municipality of Wangen-Brüttisellen in the canton of Zurich.
-
D.
Wohra
Wohra is a river in the German state of Hesse that serves as a tributary of the Ohm River.
-
E.
Wipfeld
Wipfeld is a small municipality in northern Bavaria, Germany, situated along the Main River and known for its winegrowing and historic Franconian character.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aaa66ac819082ec718e8329e0cc |
completed | April 19, 2026, 5:02 p.m. |
Created at: April 10, 2026, 10:36 a.m.