Triple
T6503550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punjabi Muslims |
E148949
|
entity |
| Predicate | majorConversionInfluence |
P9
|
FINISHED |
| Object | Sufi missionaries |
—
|
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: Sufi missionaries | Statement: [Punjabi Muslims, majorConversionInfluence, Sufi missionaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorConversionInfluence Context triple: [Punjabi Muslims, majorConversionInfluence, Sufi missionaries]
-
A.
majorFor
Indicates that an academic program, field of study, or specialization is the primary major associated with a particular student or degree.
-
B.
majorUse
Indicates that something serves as the primary or most significant use or application of an entity.
-
C.
majorImpact
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
-
D.
majorImport
Indicates that one entity is a primary or significant source of imported goods or resources for another entity.
-
E.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- 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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f386aa08190bfc8592a92ec6339 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab714908190aa7c2fbf64078e15 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:42 p.m.