Triple
T757181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chechens |
E15581
|
entity |
| Predicate | laterReligiousInfluence |
P2322
|
FINISHED |
| Object | Sufism |
—
|
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: Sufism | Statement: [Chechens, laterReligiousInfluence, Sufism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterReligiousInfluence Context triple: [Chechens, laterReligiousInfluence, Sufism]
-
A.
influencedReligion
chosen
Indicates that one entity has had a shaping or modifying effect on the religious beliefs, practices, or traditions of another entity.
-
B.
laterReligion
Indicates that one religion or religious affiliation chronologically follows or replaces another for the same entity.
-
C.
religiousTrend
Indicates a pattern or direction of change over time in religious beliefs, practices, or affiliations among entities.
-
D.
religiousCulturalContext
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
-
E.
religionHistoricallyAssociated
Indicates a historical association between an entity and a particular religion, based on past practice, tradition, or cultural linkage rather than current or official status.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66ab4608190afcd81e6606c5116 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a50348088190873a1446db657a78 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.