Triple
T24055494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilqis |
E595790
|
entity |
| Predicate | QuranicChapterNumber |
P26928
|
FINISHED |
| Object | 27 |
—
|
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: 27 | Statement: [Bilqis, QuranicChapterNumber, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: QuranicChapterNumber Context triple: [Bilqis, QuranicChapterNumber, 27]
-
A.
quranSurahNumber
chosen
Indicates the numerical position or identifier assigned to a specific surah (chapter) within the Quran.
-
B.
commandInSurah
Indicates that a particular command or directive appears within a specified surah (chapter) of the Quran.
-
C.
quranManzil
Indicates a relationship where a portion of the Quran is assigned or associated as a specific “manzil” (section) for recitation or division purposes.
-
D.
chapterAndVerse
Indicates a relationship where a specific chapter is associated with a specific verse (or set of verses) within a structured text, such as a book or document.
-
E.
quranicSurah
Indicates that one entity is a chapter (surah) of the Quran associated with or identified by the other entity.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9d65e608190b22a81ae4f94daff |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:25 p.m.