Triple
T631952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamic world |
E15944
|
entity |
| Predicate | hasLawTradition |
P17298
|
FINISHED |
| Object | Sharia |
—
|
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: Sharia | Statement: [Islamic world, hasLawTradition, Sharia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawTradition Context triple: [Islamic world, hasLawTradition, Sharia]
-
A.
coexistingLegalTradition
Indicates that multiple legal traditions or systems exist and operate simultaneously within the same social or institutional context.
-
B.
legalTraditionsTaught
Indicates that one entity teaches, covers, or includes specific legal traditions in its instruction or curriculum.
-
C.
historicalLaw
Indicates that the referenced law or legal provision existed and was in effect during a past historical period, rather than being current.
-
D.
legalDoctrine
Indicates that one legal principle, rule, or theory is being applied, referenced, or relied upon as an authoritative basis for interpreting or deciding a legal issue.
-
E.
customaryLaw
Indicates that a relationship, behavior, or rule is governed by unwritten, traditional norms and practices recognized as binding within a community or group.
- F. None of above. chosen
Provenance (4 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec2a4c08190bc5c6ce8a10b0967 |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d030c648190ba1a02301b45f694 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.