Triple
T4057910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isa |
E84737
|
entity |
| Predicate | roleForMuslims |
P2330
|
FINISHED |
| Object | model of piety and obedience to God |
—
|
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: model of piety and obedience to God | Statement: [Isa, roleForMuslims, model of piety and obedience to God]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleForMuslims Context triple: [Isa, roleForMuslims, model of piety and obedience to God]
-
A.
positionInIslam
Indicates the specific religious role, rank, or status an entity holds within the context of Islam.
-
B.
roleInIslamicLaw
Indicates the specific function, status, or authority an entity holds within the framework of Islamic legal principles and institutions.
-
C.
positionOnIslam
Indicates the stance, viewpoint, or attitude that an entity holds toward Islam.
-
D.
relationToIslam
Indicates how an entity is connected or related to Islam, such as through belief, practice, affiliation, or influence.
-
E.
religiousFunction
chosen
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbaefcb081908aab3963dcd61a20 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.