Triple
T24239189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quran 17:110 |
E603173
|
entity |
| Predicate | arabicNameOfSurah |
P51392
|
FINISHED |
| Object | سورة الإسراء |
—
|
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: سورة الإسراء | Statement: [Quran 17:110, arabicNameOfSurah, سورة الإسراء]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arabicNameOfSurah Context triple: [Quran 17:110, arabicNameOfSurah, سورة الإسراء]
-
A.
quranSurahAlternateName
Indicates that a particular name is an alternate or secondary title used to refer to a specific surah of the Quran.
-
B.
quranicSurah
Indicates that one entity is a chapter (surah) of the Quran associated with or identified by the other entity.
-
C.
subjectOfSurah
Indicates that an entity is the main topic, theme, or focus discussed within a specific surah (chapter) of the Quran.
-
D.
isMeccanSurah
Indicates that a given surah (chapter of the Qur’an) was revealed in Mecca (i.e., is classified as a Meccan surah) rather than in Medina.
-
E.
titleInArabicScript
chosen
Indicates that an entity’s title is represented in Arabic script.
- 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_69e2953f631c819097cbb421046bd417 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28a9eb68c81908a8293c00e581b41 |
completed | April 29, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:03 a.m.