Triple
T15183385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Kawthar |
E362804
|
entity |
| Predicate | verseCountRank |
P1944
|
FINISHED |
| Object | one of the shortest chapters in 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: one of the shortest chapters in the Qur’an | Statement: [Al-Kawthar, verseCountRank, one of the shortest chapters in the Qur’an]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: verseCountRank Context triple: [Al-Kawthar, verseCountRank, one of the shortest chapters in the Qur’an]
-
A.
verseCountType
Indicates the type or categorization of how verses are counted or measured in a given context.
-
B.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
C.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
D.
rankedBy
Indicates that one entity is ordered or assigned a position in a hierarchy or list according to criteria determined or applied by another entity.
-
E.
rankedAs
chosen
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006663ad48190986b680001be0e9b |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.