Triple
T20729866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emmendingen (district) |
E509544
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Emmendingen |
—
|
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: Emmendingen | Statement: [Emmendingen (district), capital, Emmendingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emmendingen Context triple: [Emmendingen (district), capital, Emmendingen]
-
A.
Emmendingen
chosen
Emmendingen is a town in southwestern Germany’s Baden-Württemberg state, known for its historic old town and location near Freiburg in the Breisgau region.
-
B.
Emmering
Emmering is a small municipality in Upper Bavaria, Germany, located in the Fürstenfeldbruck district west of Munich.
-
C.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
D.
Harksheide
Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
-
E.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ec9820819093a07f90503686b2 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:30 p.m.