Triple
T24340696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hückelhoven |
E613503
|
entity |
| Predicate | hasMunicipalPartnership |
P9362
|
FINISHED |
| Object | Kerpen |
—
|
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: Kerpen | Statement: [Hückelhoven, hasMunicipalPartnership, Kerpen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalPartnership Context triple: [Hückelhoven, hasMunicipalPartnership, Kerpen]
-
A.
hasMunicipalPartnershipWith
chosen
Indicates a formal cooperative or collaborative relationship established between two municipalities, typically involving shared projects, services, or governance initiatives.
-
B.
hasMunicipalPart
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
-
C.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
-
D.
hasCityPartner
Indicates that two cities are formally linked through a partnership, such as a sister-city or twinning relationship.
-
E.
hasMunicipalFormation
Indicates that an administrative or territorial unit is organized into, or associated with, a specific municipal formation as its local self-governing structure.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2932461ec8190933bf1e56e0f647e |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:57 a.m.