Triple
T18708801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuibenfall waterfall |
E457443
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Umhausen |
—
|
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: Umhausen | Statement: [Stuibenfall waterfall, locatedIn, Umhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umhausen Context triple: [Stuibenfall waterfall, locatedIn, Umhausen]
-
A.
Umhausen
chosen
Umhausen is a municipality in the Tyrolean Alps of western Austria, known for its scenic mountain setting and proximity to popular hiking and skiing areas.
-
B.
Wolkenstein
Wolkenstein is a historic small town in the Ore Mountains of Saxony, Germany, known for its medieval castle, spa traditions, and long association with regional mining.
-
C.
Helmbrechts
Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
-
D.
Kellenhusen
Kellenhusen is a seaside resort town on the Baltic Sea coast of northern Germany, known for its beaches and tourism.
-
E.
Gerswalde
Gerswalde is a small rural municipality in the Uckermark district of Brandenburg, northeastern Germany.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56719383481909d68c9e873ca0800 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:50 a.m.