Triple
T32556131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuscan army |
E832100
|
entity |
| Predicate | religionOfStateServed |
P198702
|
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: [Tuscan army, religionOfStateServed, Roman Catholicism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionOfStateServed Context triple: [Tuscan army, religionOfStateServed, Roman Catholicism]
-
A.
roleInStateReligion
Indicates that an entity holds a specific function, position, or involvement within the officially recognized religion of a state.
-
B.
religionDuringOffice
Indicates that a person adhered to a particular religion during the time they held a specific office or position.
-
C.
hasReligiousState
Indicates that a political entity is officially organized as, or governed according to the principles of, a particular religion.
-
D.
governsReligion
Indicates that one entity exercises authority or control over the religious practices, institutions, or beliefs associated with another entity.
-
E.
religionOfCourt
Indicates the religious affiliation associated with a particular court.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
| PDg | Predicate description generation | batch_69feff703fec8190ab7d0633e0cc5459 |
completed | May 9, 2026, 9:33 a.m. |
Created at: May 1, 2026, 1:03 a.m.