Triple
T15899721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quran 3:18 |
E385550
|
entity |
| Predicate | canonicalTextBeginsWithArabic |
P50395
|
FINISHED |
| Object | شَهِدَ اللَّهُ أَنَّهُ لَا إِلَٰهَ إِلَّا هُوَ |
—
|
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: شَهِدَ اللَّهُ أَنَّهُ لَا إِلَٰهَ إِلَّا هُوَ | Statement: [Quran 3:18, canonicalTextBeginsWithArabic, شَهِدَ اللَّهُ أَنَّهُ لَا إِلَٰهَ إِلَّا هُوَ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canonicalTextBeginsWithArabic Context triple: [Quran 3:18, canonicalTextBeginsWithArabic, شَهِدَ اللَّهُ أَنَّهُ لَا إِلَٰهَ إِلَّا هُوَ]
-
A.
hasOpeningWordsArabic
Indicates that an entity (such as a text, document, or work) has specific opening words expressed in the Arabic language.
-
B.
verseTextArabic
chosen
Indicates the Arabic-language text content associated with a specific verse in a scriptural or poetic work.
-
C.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
D.
dominantStyleForArabicTexts
Indicates the prevailing or primary stylistic form used when presenting or formatting Arabic texts.
-
E.
hasGivenNameFormInArabic
Indicates that an entity has a specific given-name form expressed in the Arabic language.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.