Triple
T1324147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aisha bint Abi Bakr |
E28286
|
entity |
| Predicate | hadithsNarrated |
P26535
|
FINISHED |
| Object | over 2000 hadiths |
—
|
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: over 2000 hadiths | Statement: [Aisha bint Abi Bakr, hadithsNarrated, over 2000 hadiths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadithsNarrated Context triple: [Aisha bint Abi Bakr, hadithsNarrated, over 2000 hadiths]
-
A.
narratedTo
Indicates that one entity tells or recounts a story, event, or information directly to another entity as the audience.
-
B.
heard
Indicates that one entity perceived a sound produced by another entity or source through hearing.
-
C.
notedIn
Indicates that information about one entity is mentioned, recorded, or referenced within another entity, such as a document, record, or source.
-
D.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
E.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19caa148190a1f5be734b7d9005 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:55 p.m.