Triple
T10992746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Personal Ordinariates |
E259788
|
entity |
| Predicate | clergyIncardination |
P96527
|
FINISHED |
| Object | into the ordinariate |
—
|
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: into the ordinariate | Statement: [Personal Ordinariates, clergyIncardination, into the ordinariate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clergyIncardination Context triple: [Personal Ordinariates, clergyIncardination, into the ordinariate]
-
A.
clergySystem
Indicates a relationship in which an organized religious institution or tradition has a structured system of clergy roles, ranks, or offices.
-
B.
clergyCan
Indicates that members of the clergy are permitted or authorized to perform a specified action or exercise a particular role or function.
-
C.
clergy
Indicates that an entity serves in an official religious or spiritual leadership role within an organized faith or religious institution.
-
D.
clergyOrder
Indicates that an individual belongs to, or is formally associated with, a specific religious clerical order or denomination.
-
E.
clergyComposition
Indicates the makeup or distribution of different types of clergy within a religious organization or context.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d32f9081909def643571499521 |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.