Triple
T22829199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karlsruhe district |
E565749
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Stutensee |
—
|
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: Stutensee | Statement: [Karlsruhe district, contains, Stutensee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stutensee Context triple: [Karlsruhe district, contains, Stutensee]
-
A.
Stutensee
chosen
Stutensee is a town in the district of Karlsruhe in the state of Baden-Württemberg in southwestern Germany.
-
B.
Pilsensee
Pilsensee is a small scenic lake in Bavaria, Germany, known for its clear waters, recreational opportunities, and location within the popular Five Lakes Region near Munich.
-
C.
Grunewaldsee
Grunewaldsee is a popular forest lake in Berlin known for its scenic surroundings and dog-friendly bathing areas.
-
D.
Weissensee
Weissensee is a picturesque alpine lake and surrounding region in southern Austria, renowned for its clear waters, outdoor recreation, and unspoiled natural landscape.
-
E.
Senftenberger See
Senftenberger See is an artificial lake in Brandenburg, Germany, created from a former open-cast lignite mine and now used as a popular recreational and water sports area.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2a0e308190941064965346f890 |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:34 p.m.