Triple
T25787330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Arba'in al-Nawawiyya |
E649454
|
entity |
| Predicate | hadith31Theme |
P169899
|
FINISHED |
| Object | no harming and no reciprocating harm |
—
|
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: no harming and no reciprocating harm | Statement: [Al-Arba'in al-Nawawiyya, hadith31Theme, no harming and no reciprocating harm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadith31Theme Context triple: [Al-Arba'in al-Nawawiyya, hadith31Theme, no harming and no reciprocating harm]
-
A.
hadith3Theme
Indicates that a hadith is associated with a particular thematic category or subject.
-
B.
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.
-
C.
hadith29Theme
Indicates that a hadith is associated with, or centers around, a particular theme or subject matter.
-
D.
hadith13Theme
Indicates that a hadith is associated with a particular theme or subject category.
-
E.
hadith1Theme
Indicates that a hadith is primarily about or centered on a particular theme or subject matter.
- 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_69f688d015908190ad5df37030ecf332 |
completed | May 2, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f688034580819086a0f9100645f8ba |
completed | May 2, 2026, 11:25 p.m. |
Created at: April 22, 2026, 5:56 a.m.