Triple
T23388661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacques Pantaléon |
E593951
|
entity |
| Predicate | memberOfClericalOrder |
P82133
|
FINISHED |
| Object | secular 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: secular clergy | Statement: [Jacques Pantaléon, memberOfClericalOrder, secular clergy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberOfClericalOrder Context triple: [Jacques Pantaléon, memberOfClericalOrder, secular clergy]
-
A.
memberOfClergy
chosen
Indicates that one entity serves in an official religious or clerical role within a religious organization or institution.
-
B.
electeeReligiousOrder
Indicates that an electee is affiliated with, or a member of, a specific religious order.
-
C.
hasClericalMember
Indicates that an entity includes or is associated with a member who performs clerical or administrative duties.
-
D.
hasClergyOrder
Indicates that an entity is associated with, or belongs to, a specific religious or clerical order.
-
E.
ordainedIn
Indicates that an individual was formally appointed or consecrated to a religious office or role at a specific place or within a particular institution.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a499bad88190afca1afb2e3fddb0 |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:35 p.m.