Triple
T22316618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kleine Emme |
E551660
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Malters |
—
|
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: Malters | Statement: [Kleine Emme, flowsThrough, Malters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malters Context triple: [Kleine Emme, flowsThrough, Malters]
-
A.
Malters
chosen
Malters is a municipality in the canton of Lucerne in central Switzerland, known for its rural character and proximity to the city of Lucerne.
-
B.
Malvy
Malvy is a French surname most notably associated with Louis Malvy, a prominent early 20th-century French politician.
-
C.
Buurmalsen
Buurmalsen is a village in the Dutch province of Gelderland, known for its rural character and location within the municipality of West Betuwe.
-
D.
Lauter
Lauter is a small municipality in the Haßberge district of Bavaria, Germany, known for its rural character and Franconian countryside setting.
-
E.
Lauter
Lauter is a small river in Germany that serves as a tributary of the Innerste.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157535eb48190adbefbb619cb5fcd |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:42 p.m.