Triple
T21590644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madinan codex order |
E532768
|
entity |
| Predicate | hasNumberOfSurahs |
P113606
|
FINISHED |
| Object | 114 |
—
|
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: 114 | Statement: [Madinan codex order, hasNumberOfSurahs, 114]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSurahs Context triple: [Madinan codex order, hasNumberOfSurahs, 114]
-
A.
numberOfSurahs
chosen
Indicates the total count of surahs associated with a given entity (such as a text, section, or collection).
-
B.
includeSurah
Indicates that one entity (such as a collection, book, or document) contains or incorporates a specific Surah as part of its contents.
-
C.
quranicSurah
Indicates that one entity is a chapter (surah) of the Quran associated with or identified by the other entity.
-
D.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
E.
quranSurahNumber
Indicates the numerical position or identifier assigned to a specific surah (chapter) within the Quran.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefadd0ec88190929c76137bd1603e |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.