Triple
T17252613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bietigheim-Bissingen |
E418793
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Bissingen an der Enz |
—
|
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: Bissingen an der Enz | Statement: [Bietigheim-Bissingen, hasSubdivision, Bissingen an der Enz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bissingen an der Enz Context triple: [Bietigheim-Bissingen, hasSubdivision, Bissingen an der Enz]
-
A.
Bissingen
Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
-
B.
Bissingen
chosen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
C.
Biberach an der Riß
Biberach an der Riß is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval old town and traditional Swabian culture.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6a1b648190a8bb2deb67bbdfdc |
completed | April 19, 2026, 1:22 a.m. |
Created at: April 10, 2026, 5:39 a.m.