Triple
T25787333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Arba'in al-Nawawiyya |
E649454
|
entity |
| Predicate | hadith34Theme |
P170939
|
FINISHED |
| Object | commanding good and forbidding evil |
—
|
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: commanding good and forbidding evil | Statement: [Al-Arba'in al-Nawawiyya, hadith34Theme, commanding good and forbidding evil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadith34Theme Context triple: [Al-Arba'in al-Nawawiyya, hadith34Theme, commanding good and forbidding evil]
-
A.
hadith3Theme
Indicates that a hadith is associated with a particular thematic category or subject.
-
B.
hadith32Theme
Indicates that something is identified as a central topic, subject, or thematic focus of Hadith 32.
-
C.
hadith33Theme
Indicates that a hadith is associated with a particular theme or subject matter.
-
D.
hadith31Theme
Indicates that a subject (such as a text, discussion, or classification) is thematically related to the content or teachings of Hadith 31.
-
E.
hadith30Theme
Indicates that a subject (such as a text, narration, or discussion) is about, or centrally concerns, the theme or main topic associated with Hadith 30.
- 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_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 22, 2026, 5:56 a.m.