Triple
T35026685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quran 83:2 |
E1010355
|
entity |
| Predicate | hasTafsir |
P75789
|
FINISHED |
| Object | classical exegesis by scholars such as al-Tabari |
—
|
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: classical exegesis by scholars such as al-Tabari | Statement: [Quran 83:2, hasTafsir, classical exegesis by scholars such as al-Tabari]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTafsir Context triple: [Quran 83:2, hasTafsir, classical exegesis by scholars such as al-Tabari]
-
A.
نوع_التفسير
Indicates the specific type or category of interpretation being applied to something.
-
B.
hasQuranicEquivalent
Indicates that something has a corresponding or analogous concept, term, or passage found in the Quran.
-
C.
hasExegesisBy
chosen
Indicates that an entity (such as a text or passage) is the subject of an exegesis authored or provided by another entity.
-
D.
hasQuranicDescription
Indicates that there exists a description or characterization of the subject that is explicitly given or referenced in the Quran.
-
E.
له_شروح
Indicates that something (typically a text, concept, or work) has one or more explanations or commentaries associated with it.
- 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_69f76dccf0108190af43b465d3750196 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:01 p.m.