Triple
T1687499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah An-Nur |
E36475
|
entity |
| Predicate | addressesIncident |
P3847
|
FINISHED |
| Object | slander against Aisha bint Abi Bakr |
—
|
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: slander against Aisha bint Abi Bakr | Statement: [Surah An-Nur, addressesIncident, slander against Aisha bint Abi Bakr]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressesIncident Context triple: [Surah An-Nur, addressesIncident, slander against Aisha bint Abi Bakr]
-
A.
address
Indicates that one entity directs spoken or written communication specifically to another entity.
-
B.
addresses
Indicates that one entity directs speech, communication, or written correspondence specifically toward another entity.
-
C.
addressContext
Indicates the situational or conversational setting in which an address (such as a location, contact, or reference) is used or interpreted.
-
D.
apseLocation
Indicates the specific place or position where an apse is situated within a larger structure or context.
-
E.
addressesIssue
chosen
Indicates that one entity deals with, responds to, or attempts to resolve a specific issue associated with another entity.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69aa61b71cec8190b273588051058ebd |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.