Triple
T19869803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B33 road |
E477482
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Allensbach |
—
|
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: Allensbach | Statement: [B33 road, passesThrough, Allensbach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allensbach Context triple: [B33 road, passesThrough, Allensbach]
-
A.
Allensbach
chosen
Allensbach is a municipality in the German state of Baden-Württemberg, situated on the shores of Lake Constance and known for hosting the Allensbach Institute for Public Opinion Research.
-
B.
Calmbach
Calmbach is a small town in Germany’s Black Forest region, known for its scenic location in the Enz Valley and traditional spa and nature tourism.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Bergneustadt
Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
-
E.
Faulbach
Faulbach is a district (Ortsteil) of the town of Hadamar in the Limburg-Weilburg district of Hesse, Germany.
- 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.