Triple
T24035253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Copiapó |
E595213
|
entity |
| Predicate | coPatron |
P154600
|
FINISHED |
| Object | Our Lady of the Rosary |
—
|
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: Our Lady of the Rosary | Statement: [Diocese of Copiapó, coPatron, Our Lady of the Rosary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coPatron Context triple: [Diocese of Copiapó, coPatron, Our Lady of the Rosary]
-
A.
patronType
Indicates the classification or category of a patron in relation to a service, institution, or resource.
-
B.
laterPatron
Indicates that one entity serves as a patron of another at a later time than some reference patronage relationship.
-
C.
usedAsPatronOf
Indicates that one entity serves as a patron or sponsor for another, providing support, endorsement, or backing.
-
D.
primaryPatron
Indicates that one entity serves as the main or chief supporter, sponsor, or benefactor of another entity.
-
E.
cityPatron
Indicates that one entity serves as the patron, protector, or special guardian of a particular city.
- F. None of above. chosen
Provenance (4 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d273d88190b0762f1ee317d811 |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 9:56 p.m.