Triple
T28370170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Kleve |
E718602
|
entity |
| Predicate | hasBorderWithDistrict |
P224
|
FINISHED |
| Object | Kreis Wesel |
—
|
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: Kreis Wesel | Statement: [Kreis Kleve, hasBorderWithDistrict, Kreis Wesel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderWithDistrict Context triple: [Kreis Kleve, hasBorderWithDistrict, Kreis Wesel]
-
A.
isBorderDistrict
Indicates that a district is located along and directly borders the boundary of a larger administrative region or country.
-
B.
isBorderMunicipality
Indicates that a municipality is located on or directly adjacent to the border of a larger administrative region, country, or jurisdiction.
-
C.
hasBorderCity
Indicates that one location is a city situated on or very near the border of another geographic or political region.
-
D.
borderedBy
chosen
Indicates that one entity shares a common boundary or edge with another entity.
-
E.
hasNearbyCountyBorder
Indicates that the borders of two counties are geographically close to each other, though not necessarily directly adjacent.
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: April 28, 2026, 12:59 a.m.