Triple
T36406174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic root R-Š-D (رشَد) |
E896753
|
entity |
| Predicate | quranicConcept |
P175747
|
FINISHED |
| Object | right guidance from God |
—
|
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: right guidance from God | Statement: [Arabic root R-Š-D (رشَد), quranicConcept, right guidance from God]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quranicConcept Context triple: [Arabic root R-Š-D (رشَد), quranicConcept, right guidance from God]
-
A.
quranicContext
Indicates that something is situated within, derived from, or directly related to the textual, historical, or thematic context of the Quran.
-
B.
quranicPhrase
Indicates that one entity is a phrase or expression that appears in, or is directly derived from, the Quran.
-
C.
quranicDescription
Indicates that one entity is described, characterized, or referenced within the text of the Quran in relation to another entity.
-
D.
quranicTermType
chosen
Indicates the classification relationship that specifies what type or category a given Qur'anic term belongs to.
-
E.
quranicOppositeTerm
Indicates that one term is presented in the Quran as the conceptual or semantic opposite of another term.
- 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_69f76e53b81081908d3b81860593f38a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.