Triple
T21706952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taraweeh prayers |
E535794
|
entity |
| Predicate | recitationLength |
P145019
|
FINISHED |
| Object | long portions of the Qur’an |
—
|
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: long portions of the Qur’an | Statement: [Taraweeh prayers, recitationLength, long portions of the Qur’an]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recitationLength Context triple: [Taraweeh prayers, recitationLength, long portions of the Qur’an]
-
A.
recitationObject
Indicates that something is the content or material being recited in a recitation event.
-
B.
recitationRecommended
Indicates that a particular recitation session or section is recommended for an entity, such as a student or course.
-
C.
recitationRecommendedAfter
Indicates that one item is advised or suggested to be recited after another in a recommended sequence.
-
D.
recitationStructure
Indicates the structural or organizational relationship between parts of a recitation (such as sections, verses, or segments) and how they are arranged or ordered.
-
E.
recitationSetting
Indicates the context or environment in which a recitation takes place, such as the type, location, or format of the recitation event.
- 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb530779c819080204c3bd2f6afa2 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:46 p.m.