Triple
T14094070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pima Revolt of 1751 |
E339204
|
entity |
| Predicate | hasReligionInvolved |
P72520
|
FINISHED |
| Object | 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: Catholicism | Statement: [Pima Revolt of 1751, hasReligionInvolved, Catholicism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligionInvolved Context triple: [Pima Revolt of 1751, hasReligionInvolved, Catholicism]
-
A.
involvedReligion
chosen
Indicates that an entity is associated with, participates in, or is characterized by a particular religion.
-
B.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
-
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.
hasReligiousMovement
Indicates that an entity is associated with, follows, or is characterized by a particular religious movement.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fb7fb3c819083266dbe7e93aaff |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.