Triple
T9440785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augsburg district |
E227639
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Schmutter |
E748957
|
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: Schmutter | Statement: [Augsburg district, hasRiver, Schmutter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schmutter Context triple: [Augsburg district, hasRiver, Schmutter]
-
A.
Schmutter
chosen
The Schmutter is a river in Bavaria, Germany, known as a regional tributary that flows through the Swabian landscape before joining the Wertach.
-
B.
Mürzzuschlag
Mürzzuschlag is a small Austrian town in the state of Styria, known historically for its iron industry and as a winter sports and railway hub in the Eastern Alps.
-
C.
Unterdießen
Unterdießen is a small municipality in the district of Landsberg am Lech in Bavaria, Germany.
-
D.
Schmarbeck
Schmarbeck is a small watercourse in Lower Saxony, Germany, known as one of the minor streams feeding into the Örtze River within the Lüneburg Heath region.
-
E.
Flaemmchen
Flaemmchen is a young, ambitious stenographer and aspiring actress in Vicki Baum’s novel (and its film adaptation) "Grand Hotel," representing the struggles and dreams of working-class women in Weimar-era Berlin.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee4f4a08190ada5ee14fec2b822 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1105dc6b48190bd6c7d932d9f48d5 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:50 p.m.