Triple
T24283133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night of Measure |
E605595
|
entity |
| Predicate | hasQuranicChapter |
P6720
|
FINISHED |
| Object | Surah 97 (al-Qadr) |
—
|
NE NERFINISHED |
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: Surah 97 (al-Qadr) | Statement: [Night of Measure, hasQuranicChapter, Surah 97 (al-Qadr)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQuranicChapter Context triple: [Night of Measure, hasQuranicChapter, Surah 97 (al-Qadr)]
-
A.
hasQuranicVerseReference
Indicates that an entity is associated with, or refers to, a specific verse or verses from the Quran.
-
B.
hasVersesBy
Indicates a relationship where a work, such as a song or poem, contains verses authored or written by a specific creator.
-
C.
hasVersesIn
Indicates that one entity (typically a text, chapter, or section) contains or is composed of verses found within another entity (such as a book, collection, or scripture).
-
D.
containsChapter
chosen
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
E.
quranicChapterType
Indicates the classification relationship that specifies what type or category a given Quranic chapter belongs to.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f53a8448190b66f6a97544bacc1 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.