Triple
T7253684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regnans in Excelsis |
E157665
|
entity |
| Predicate | religiousImpactOn |
P48954
|
FINISHED |
| Object | English Catholics |
—
|
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: English Catholics | Statement: [Regnans in Excelsis, religiousImpactOn, English Catholics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousImpactOn Context triple: [Regnans in Excelsis, religiousImpactOn, English Catholics]
-
A.
influencedReligion
Indicates that one entity has had a shaping or modifying effect on the religious beliefs, practices, or traditions of another entity.
-
B.
influencedByReligion
Indicates that an entity’s characteristics, decisions, or development are shaped or affected by religious beliefs, practices, or institutions.
-
C.
religiousReformImpact
chosen
Indicates the effect that a religious reform has on beliefs, practices, institutions, or social structures.
-
D.
denominationalImpact
Indicates how a particular denomination influences, shapes, or affects another entity, group, or context.
-
E.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea9d41908190bb76c6a5b9d5b1a2 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.