Triple
T14251319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sprockhövel |
E353269
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Niedersprockhövel |
E353269
|
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: Niedersprockhövel | Statement: [Sprockhövel, hasSubdivision, Niedersprockhövel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niedersprockhövel Context triple: [Sprockhövel, hasSubdivision, Niedersprockhövel]
-
A.
Sprockhövel
chosen
Sprockhövel is a small town in North Rhine-Westphalia, Germany, known for its historical coal mining heritage and location in the hilly Ruhr region.
-
B.
Meinerzhagen
Meinerzhagen is a town in western Germany known for its location in the hilly, forested Sauerland region of North Rhine-Westphalia.
-
C.
Dülmen
Dülmen is a town in western Germany’s North Rhine-Westphalia, known for its location between Münster and the Ruhr area and for the wild Dülmen ponies in the nearby nature reserve.
-
D.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
E.
Göhrde
Göhrde is a municipality in Lower Saxony, Germany, known for its extensive forested areas and historical royal hunting grounds.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6296f9d0819086f62f525d07eb12 |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd325815d48190b070866f41986847 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:08 a.m.