Triple
T36444225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quran 49:2 |
E897822
|
entity |
| Predicate | contextualThemeInSurah |
P114772
|
FINISHED |
| Object | social manners and community ethics |
—
|
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: social manners and community ethics | Statement: [Quran 49:2, contextualThemeInSurah, social manners and community ethics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contextualThemeInSurah Context triple: [Quran 49:2, contextualThemeInSurah, social manners and community ethics]
-
A.
themeInQuran
Indicates that a particular theme, concept, or topic is present in and addressed by the Quran.
-
B.
quranicContext
Indicates that something is situated within, derived from, or directly related to the textual, historical, or thematic context of the Quran.
-
C.
subjectOfSurah
chosen
Indicates that an entity is the main topic, theme, or focus discussed within a specific surah (chapter) of the Quran.
-
D.
quranicDerivative
Indicates that one entity is a linguistic form or term derived from, based on, or morphologically related to a word or concept found in the Quran.
-
E.
hadith1Theme
Indicates that a hadith is primarily about or centered on a particular theme or subject matter.
- 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_69f76e5720b481908f8177ac24a7560b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:10 p.m.