Triple
T10992747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Personal Ordinariates |
E259788
|
entity |
| Predicate | laityEnrollment |
P69269
|
FINISHED |
| Object | by petition and acceptance |
—
|
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: by petition and acceptance | Statement: [Personal Ordinariates, laityEnrollment, by petition and acceptance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laityEnrollment Context triple: [Personal Ordinariates, laityEnrollment, by petition and acceptance]
-
A.
hasViewOnLaity
Indicates that one entity holds a particular stance, opinion, or doctrinal position regarding the role or nature of laypeople.
-
B.
enrollment
Indicates the formal act of registering or being registered in a course, program, or institution, establishing an official participant–provider relationship.
-
C.
enrollmentSize
Indicates the number of individuals enrolled or registered in a particular group, program, or institution.
-
D.
enrollmentLevel
Indicates the degree or status of participation an entity has in a particular enrollment context (such as a program, course, or service).
-
E.
enrollmentCategory
chosen
Indicates the classification or type of enrollment under which an entity is registered or participating.
- 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_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. |
Created at: April 8, 2026, 9:24 p.m.