Triple
T25090677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheda-Wiedenbrück |
E628446
|
entity |
| Predicate | hasTownPart |
P847
|
FINISHED |
| Object | Wiedenbrück |
—
|
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: Wiedenbrück | Statement: [Rheda-Wiedenbrück, hasTownPart, Wiedenbrück]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTownPart Context triple: [Rheda-Wiedenbrück, hasTownPart, Wiedenbrück]
-
A.
hasTown
chosen
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
B.
hasTownship
Indicates that one administrative area or jurisdiction includes or is associated with a specific township.
-
C.
hasMunicipalPart
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
-
D.
isInteriorTownOf
Indicates that one town is located within the interior region of, and is administratively or geographically associated with, a larger area or jurisdiction.
-
E.
hasNeighborhoodPart
Indicates that one entity is a spatially adjacent or locally contained part of another entity, typically within its surrounding neighborhood or vicinity.
- F. None of above.
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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 18, 2026, 6:24 a.m.