Triple
T35109979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of San Paolo alla Regola |
E1013257
|
entity |
| Predicate | hasClericalAdministration |
P9815
|
FINISHED |
| Object | Roman Catholic clergy |
—
|
LITERAL FINISHED |
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: Roman Catholic clergy | Statement: [Church of San Paolo alla Regola, hasClericalAdministration, Roman Catholic clergy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClericalAdministration Context triple: [Church of San Paolo alla Regola, hasClericalAdministration, Roman Catholic clergy]
-
A.
hasClericalFunction
Indicates that an entity performs, is responsible for, or is associated with a clerical or administrative function.
-
B.
hasClericalAssociation
Indicates a relationship in which an entity is connected to or involved with clerical roles, duties, or religious office.
-
C.
hasClericalMember
Indicates that an entity includes or is associated with a member who performs clerical or administrative duties.
-
D.
hasClericalStructure
Indicates that an entity possesses an organized clerical or administrative hierarchy or framework.
-
E.
hasClergy
chosen
Indicates that an organization or institution possesses or is served by members of the clergy.
- 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_69f76dd659d08190bcdc00d37caafb62 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
Created at: May 3, 2026, 4:01 p.m.