Triple
T10616916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Swabia |
E276143
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Biberach an der Riß |
E381274
|
NE FINISHED |
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: Biberach an der Riß | Statement: [Upper Swabia, contains, Biberach an der Riß]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biberach an der Riß Context triple: [Upper Swabia, contains, Biberach an der Riß]
-
A.
Biberach an der Riß
chosen
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.
-
B.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
C.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
-
D.
Bochingen
Bochingen is a village and district of the town Oberndorf am Neckar in the state of Baden-Württemberg in southwestern Germany.
-
E.
Baiersbronn
Baiersbronn is a municipality in Germany’s Black Forest renowned for its scenic landscapes and high concentration of Michelin-starred restaurants.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df6e2df4819099a19b59d90d0dd1 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d448fac81909137b0a0ed9b976e |
completed | April 19, 2026, 1:17 a.m. |
Created at: April 8, 2026, 7:33 p.m.