Triple
T34754629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quran 83:9 |
E1001882
|
entity |
| Predicate | exegesisSubject |
P181577
|
FINISHED |
| Object | Tafsir literature |
—
|
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: Tafsir literature | Statement: [Quran 83:9, exegesisSubject, Tafsir literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exegesisSubject Context triple: [Quran 83:9, exegesisSubject, Tafsir literature]
-
A.
styleOfExegesis
Indicates the particular interpretive method or approach applied when analyzing or explaining a text.
-
B.
scripturalExpertise
Indicates a relationship where one entity possesses specialized knowledge or authoritative understanding of religious scriptures in relation to another entity or context.
-
C.
hasExegesisBy
Indicates that an entity (such as a text or passage) is the subject of an exegesis authored or provided by another entity.
-
D.
inScripture
Indicates that something is mentioned, described, or referenced within a scriptural or sacred text.
-
E.
scriptureAllusion
Indicates that one entity makes reference to, echoes, or is inspired by a passage, theme, or element from a scriptural text found in another entity.
- 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_69f76db0fb30819096709d43f9a1f45f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77ff804f08190b431a31e6179ace4 |
completed | May 3, 2026, 5:03 p.m. |
Created at: May 3, 2026, 3:59 p.m.