Triple
T2537470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish Rebellion of 1641 |
E56301
|
entity |
| Predicate | hasReligionAspect |
P24743
|
FINISHED |
| Object | Catholic–Protestant conflict |
—
|
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: Catholic–Protestant conflict | Statement: [Irish Rebellion of 1641, hasReligionAspect, Catholic–Protestant conflict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligionAspect Context triple: [Irish Rebellion of 1641, hasReligionAspect, Catholic–Protestant conflict]
-
A.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
B.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
C.
recognizesReligion
Indicates that one entity formally acknowledges or accepts another entity as a valid or legitimate religion.
-
D.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
-
E.
hasReligiousTheme
chosen
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd64a2194819097c66cbeb37fe859 |
completed | March 7, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69abd0c4a5dc819097812db50443420a |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.