Triple
T2047830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunan al-Nasa’i |
E45493
|
entity |
| Predicate | hasApproximateNumberOfHadith |
P26982
|
FINISHED |
| Object | around 5700 in common prints |
—
|
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: around 5700 in common prints | Statement: [Sunan al-Nasa’i, hasApproximateNumberOfHadith, around 5700 in common prints]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfHadith Context triple: [Sunan al-Nasa’i, hasApproximateNumberOfHadith, around 5700 in common prints]
-
A.
hadithNarrationsCountApprox
chosen
Indicates an approximate number of hadith narrations associated with an entity.
-
B.
hadithStatus
Indicates the classification or evaluation of a hadith’s authenticity or reliability within a given scholarly or doctrinal framework.
-
C.
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).
-
D.
narratedHadith
Indicates that one entity transmitted or reported a hadith (a prophetic narration) from or about another entity.
-
E.
basedOnHadith
Indicates that something is derived from, supported by, or directly referencing a specific 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb974e8488190887b840c2cb88b3a |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:39 p.m.