Triple
T10616920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Swabia |
E276143
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bad Saulgau |
E727131
|
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: Bad Saulgau | Statement: [Upper Swabia, contains, Bad Saulgau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Saulgau Context triple: [Upper Swabia, contains, Bad 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.
Aumetz
Aumetz is a commune in northeastern France, located in the Moselle department near the border with Luxembourg.
-
C.
Rolandseck
Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
-
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.
Rixheim
Rixheim is a commune in northeastern France’s Grand Est region, known historically for its wallpaper manufacturing industry.
- 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_69d9989a7aec8190bcf06a93da61647d |
completed | April 11, 2026, 12:40 a.m. |
Created at: April 8, 2026, 7:33 p.m.