Triple
T24340697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hückelhoven |
E613503
|
entity |
| Predicate | hasFriendshipCityRelationship |
P143078
|
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, hasFriendshipCityRelationship, Kerpen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFriendshipCityRelationship Context triple: [Hückelhoven, hasFriendshipCityRelationship, Kerpen]
-
A.
friendshipCityOf
Indicates a relationship where a city is identified as the place associated with a friendship, such as where the friendship originated, is based, or is primarily maintained.
-
B.
hasSisterCityRelationshipType
Indicates a formal sister-city partnership relationship that exists between two municipalities or cities.
-
C.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
-
D.
hasFriendshipPactWith
chosen
Indicates a mutual agreement or bond of friendship established between two entities.
-
E.
hasSisterCityRelationReason
Indicates that there is a specific reason or justification for the existence of a sister city relationship between two places.
- 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.