Triple
T10834670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diemel |
E255721
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Marsberg |
E564065
|
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: Marsberg | Statement: [Diemel, passesThrough, Marsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marsberg Context triple: [Diemel, passesThrough, Marsberg]
-
A.
Marsberg
chosen
Marsberg is a small town in the eastern part of North Rhine-Westphalia, Germany, known for its historic architecture and scenic location in the Sauerland region.
-
B.
Nyhausen
Nyhausen is a locality in Germany historically noted as the birthplace of the Swedish nobleman and soldier Philip Christoph von Königsmarck.
-
C.
Bergneustadt
Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
-
D.
Brannenburg
Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
-
E.
Osterburg
Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d74425447081908fb51c7edf54af67 |
completed | April 9, 2026, 6:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb11a264c8190829ff89f0b13d063 |
completed | April 14, 2026, 9:26 p.m. |
Created at: April 8, 2026, 9:19 p.m.