Triple
T24406526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usuli school |
E615325
|
entity |
| Predicate | viewOnTextualSources |
P45238
|
FINISHED |
| Object | uses Qurʾan, hadith, consensus, and reason as sources |
—
|
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: uses Qurʾan, hadith, consensus, and reason as sources | Statement: [Usuli school, viewOnTextualSources, uses Qurʾan, hadith, consensus, and reason as sources]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOnTextualSources Context triple: [Usuli school, viewOnTextualSources, uses Qurʾan, hadith, consensus, and reason as sources]
-
A.
viewOnSources
chosen
Indicates that an entity’s perspective, opinion, or interpretation is based on, derived from, or informed by specific source materials.
-
B.
viewOnGeneralTexts
Indicates that an entity is permitted to access or read general, non-specialized textual content.
-
C.
textSources
Indicates that one entity serves as a source or origin for the text content associated with another entity.
-
D.
viewOnKnowledge
Indicates the perspective, stance, or opinion one entity holds regarding another entity’s knowledge or understanding.
-
E.
viewOnMatter
Indicates a stance, opinion, or perspective that one entity holds regarding a particular issue, topic, or matter.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294dfd8d88190b831b6a8f4157980 |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.