Triple
T33051543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | طور |
E845735
|
entity |
| Predicate | hasQuranicVerseCountApprox |
P7673
|
FINISHED |
| Object | مذكور في عدة مواضع من القرآن |
—
|
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: مذكور في عدة مواضع من القرآن | Statement: [طور, hasQuranicVerseCountApprox, مذكور في عدة مواضع من القرآن]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQuranicVerseCountApprox Context triple: [طور, hasQuranicVerseCountApprox, مذكور في عدة مواضع من القرآن]
-
A.
hasQuranicVerseReference
Indicates that an entity is associated with, or refers to, a specific verse or verses from the Quran.
-
B.
approximateNumberOfVerses
chosen
Indicates an estimated or approximate count of verses associated with an entity.
-
C.
numberOfSurahs
Indicates the total count of surahs associated with a given entity (such as a text, section, or collection).
-
D.
hasVersesBy
Indicates a relationship where a work, such as a song or poem, contains verses authored or written by a specific creator.
-
E.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
- 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:24 a.m.