Triple
T2788544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Abasa |
E61869
|
entity |
| Predicate | numberOfRukus |
P43587
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Surah Abasa, numberOfRukus, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRukus Context triple: [Surah Abasa, numberOfRukus, 1]
-
A.
hasRuku
Indicates that an entity performs, contains, or is associated with a ruku (the bowing posture/section) within a prayer or recitation structure.
-
B.
rukus
Indicates that an entity is associated with or participates in a disturbance, commotion, or noisy disruptive event involving another entity.
-
C.
numberOfRakats
Indicates the specific count of prayer units (rakats) associated with a given prayer or ritual act.
-
D.
numberOfRings
Indicates the quantity of rings associated with an entity.
-
E.
numberOfMonksApprox
Indicates an approximate count or estimate of how many monks are involved or present in a given context.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 9:58 p.m.