Triple
T1988065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sahih al-Bukhari |
E43185
|
entity |
| Predicate | approximateNumberOfHadith |
P26982
|
FINISHED |
| Object | over 7000 with repetitions |
—
|
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 7000 with repetitions | Statement: [Sahih al-Bukhari, approximateNumberOfHadith, over 7000 with repetitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfHadith Context triple: [Sahih al-Bukhari, approximateNumberOfHadith, over 7000 with repetitions]
-
A.
hadithNarrationsCountApprox
chosen
Indicates an approximate number of hadith narrations associated with an entity.
-
B.
approximateNumberOfVerses
Indicates an estimated or approximate count of verses associated with an entity.
-
C.
approximateNumberOfTractates
Indicates a relationship where an entity is associated with an estimated or non-exact count of tractates linked to it.
-
D.
basedOnHadith
Indicates that something is derived from, supported by, or directly referencing a specific hadith.
-
E.
hadithStatus
Indicates the classification or evaluation of a hadith’s authenticity or reliability within a given scholarly or doctrinal framework.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.