Triple
T10992734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Personal Ordinariates |
E259788
|
entity |
| Predicate | haveOwnSeminaryArrangements |
P96523
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Personal Ordinariates, haveOwnSeminaryArrangements, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveOwnSeminaryArrangements Context triple: [Personal Ordinariates, haveOwnSeminaryArrangements, yes]
-
A.
hasMinorSeminary
Indicates that an entity operates, is associated with, or possesses a minor seminary as part of its organizational structure or activities.
-
B.
hasMajorSeminary
Indicates that an institution or entity possesses or is associated with a major seminary for advanced clerical or theological training.
-
C.
seminaryName
Indicates the name assigned to a seminary institution.
-
D.
hasParochialSchool
Indicates that an entity operates, is associated with, or includes a parochial (religious-affiliated) school.
-
E.
hasChurch
Indicates that a place or entity possesses, contains, or is associated with a church.
- 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.