Triple
T21288660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emscher |
E524728
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Bottrop |
—
|
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: Bottrop | Statement: [Emscher, flowsThrough, Bottrop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bottrop Context triple: [Emscher, flowsThrough, Bottrop]
-
A.
Bottrop
chosen
Bottrop is a city in western Germany’s Ruhr area, historically shaped by coal mining and industry.
-
B.
Ruhrort
Ruhrort is a historic inland port district of Duisburg in western Germany, known for its major role in Rhine and Ruhr river shipping and industry.
-
C.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
D.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
E.
Nettetal
Nettetal is a town in western Germany’s North Rhine-Westphalia, known for its lakes and nature reserves near the Dutch border.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d882408190a2300327cb73b7f6 |
completed | April 21, 2026, 8:35 a.m. |
Created at: April 16, 2026, 4:03 p.m.