Triple
T7347894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shariah supervisory boards |
E169423
|
entity |
| Predicate | helpsMitigate |
P20171
|
FINISHED |
| Object | Shariah non-compliance risk |
—
|
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: Shariah non-compliance risk | Statement: [Shariah supervisory boards, helpsMitigate, Shariah non-compliance risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsMitigate Context triple: [Shariah supervisory boards, helpsMitigate, Shariah non-compliance risk]
-
A.
especiallyHelpsWhen
Indicates that one entity is particularly beneficial or effective in assisting another entity or situation under certain conditions or circumstances.
-
B.
helpedSecure
Indicates that one entity contributed to obtaining, protecting, or ensuring the safety or stability of another entity or outcome.
-
C.
hasEnvironmentalMitigation
Indicates that an entity has associated measures, actions, or features intended to reduce, offset, or manage its negative environmental impacts.
-
D.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
E.
providesProtectionAgainst
chosen
Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f139505c8190a7158cf59a6e089e |
completed | March 27, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69c6f02aeeb8819099d1626566cec18b |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:05 p.m.