Triple
T8337636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hattingen |
E195827
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object | River Ruhr |
E80553
|
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: River Ruhr | Statement: [Hattingen, locatedOn, River Ruhr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: River Ruhr Context triple: [Hattingen, locatedOn, River Ruhr]
-
A.
Ruhr
chosen
The Ruhr is a river in western Germany that flows through the Ruhr industrial region before joining the Rhine.
-
B.
Rhine
The Rhine is one of Europe's most important rivers, historically serving as a vital trade route and cultural boundary from the Alps through Germany to the North Sea.
-
C.
Rhein II
Rhein II is a large-scale color photograph by German visual artist Andreas Gursky, renowned for its minimalist depiction of the Rhine River and for once being the most expensive photograph ever sold at auction.
-
D.
Rheine
Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
-
E.
Weser
The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd5027c81909724f25aa30bbe58 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05bdc87fc8190a5ae0883742cb08c |
completed | April 4, 2026, 12:31 a.m. |
Created at: March 30, 2026, 5:57 p.m.