Triple
T19869808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B33 road |
E477482
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Saulgau |
—
|
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: Saulgau | Statement: [B33 road, passesThrough, Saulgau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saulgau Context triple: [B33 road, passesThrough, Saulgau]
-
A.
Bad Saulgau
chosen
Bad Saulgau is a spa town in the district of Sigmaringen in Baden-Württemberg, Germany, known for its thermal baths and historic town center.
-
B.
Lombach
The Lombach is a small river in the Bernese Oberland region of Switzerland that flows through the municipality of Unterseen near Interlaken.
-
C.
Willanzheim
Willanzheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian wine-growing tradition.
-
D.
Forbach
Forbach is a town in northeastern France near the German border, known historically for its coal mining industry and cross-border cultural ties.
-
E.
Forbach
Forbach is a picturesque village in Germany’s Black Forest region, known for its traditional wooden bridge, historic church, and scenic location along the Murg River.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a2cc8481908d134b0b5cf79d06 |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.