Triple
T7704909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Reformation |
E174588
|
entity |
| Predicate | hasOpposingReligion |
P28124
|
FINISHED |
| Object | Roman Catholicism |
—
|
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: Roman Catholicism | Statement: [French Reformation, hasOpposingReligion, Roman Catholicism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposingReligion Context triple: [French Reformation, hasOpposingReligion, Roman Catholicism]
-
A.
primaryOpponentsReligion
chosen
Indicates the religion or belief system followed by an entity’s main or primary opponent.
-
B.
hasSecondaryReligion
Indicates that an entity practices, adheres to, or is associated with a secondary religion in addition to its primary religion.
-
C.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
D.
hadViewOnReligion
Indicates that an entity held a particular perspective, belief, or stance regarding religion.
-
E.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
- 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_69c6995b3e8c8190833108f883d5f53c |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c70165e78c8190bf6b3c34e243cb81 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:03 p.m.