Triple
T9219801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الجامع الصحيح |
E221332
|
entity |
| Predicate | عدد_الأحاديث_بالأصول |
P26982
|
FINISHED |
| Object | نحو 2600 حديث بلا تكرار |
—
|
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: نحو 2600 حديث بلا تكرار | Statement: [الجامع الصحيح, عدد_الأحاديث_بالأصول, نحو 2600 حديث بلا تكرار]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: عدد_الأحاديث_بالأصول Context triple: [الجامع الصحيح, عدد_الأحاديث_بالأصول, نحو 2600 حديث بلا تكرار]
-
A.
hadithNarrationsCountApprox
chosen
Indicates an approximate number of hadith narrations associated with an entity.
-
B.
sourceOfHadithFor
Indicates that one entity serves as the originating source or transmitter for a particular hadith associated with another entity.
-
C.
narratedHadith
Indicates that one entity transmitted or reported a hadith (a prophetic narration) from or about another entity.
-
D.
numberOfSutras
Indicates the quantity or count of sutras associated with a given entity.
-
E.
hadithsNarrated
Indicates that one entity (typically a person) has narrated, transmitted, or reported the hadiths associated with another entity (such as a collection, text, or individual hadith).
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda74808081908d4bf890759e7120 |
completed | April 1, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:28 p.m.