Triple
T25787307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Arba'in al-Nawawiyya |
E649454
|
entity |
| Predicate | hadith7Theme |
P161478
|
FINISHED |
| Object | religion as sincere advice |
—
|
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: religion as sincere advice | Statement: [Al-Arba'in al-Nawawiyya, hadith7Theme, religion as sincere advice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadith7Theme Context triple: [Al-Arba'in al-Nawawiyya, hadith7Theme, religion as sincere advice]
-
A.
hadith6Theme
Indicates that a hadith is associated with a particular thematic category or subject matter.
-
B.
hadith1Theme
Indicates that a hadith is primarily about or centered on a particular theme or subject matter.
-
C.
hadith3Theme
Indicates that a hadith is associated with a particular thematic category or subject.
-
D.
themeInQuran
Indicates that a particular theme, concept, or topic is present in and addressed by the Quran.
-
E.
hadithCategory
Indicates that a hadith is classified under a particular category or type within hadith literature.
- F. None of above. chosen
Provenance (4 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_69e7ab33e9308190afe415dc6f9e8876 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f613bc641c819084343cc78d080640 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f613502d808190b89927e5e734b43a |
completed | May 2, 2026, 3:08 p.m. |
Created at: April 22, 2026, 5:56 a.m.