Triple
T1288788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Society of Saint Pius X |
E27496
|
entity |
| Predicate | grantedFacultyBy |
P2246
|
FINISHED |
| Object | Pope Francis to validly hear confessions |
—
|
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: Pope Francis to validly hear confessions | Statement: [Society of Saint Pius X, grantedFacultyBy, Pope Francis to validly hear confessions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantedFacultyBy Context triple: [Society of Saint Pius X, grantedFacultyBy, Pope Francis to validly hear confessions]
-
A.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
-
B.
grantedByInstitution
Indicates that something (such as a status, permission, or resource) is conferred or authorized by an institution.
-
C.
publicUniversityFaculty
Indicates that a person is a member of the faculty (e.g., professor, lecturer, instructor) at a public university.
-
D.
hasFacultyType
Indicates that a faculty member or academic unit is associated with a specific category or type of faculty (e.g., full-time, adjunct, visiting).
-
E.
grantedBy
chosen
Indicates that a right, permission, or benefit is conferred or authorized by one entity to another.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d38d7c81908941edda9cac5d6a |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.