Triple
T389117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Classical Arabic |
E8842
|
entity |
| Predicate | hasNormativeSource |
P9326
|
FINISHED |
| Object | language of the Quran |
—
|
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: language of the Quran | Statement: [Classical Arabic, hasNormativeSource, language of the Quran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNormativeSource Context triple: [Classical Arabic, hasNormativeSource, language of the Quran]
-
A.
hasNominativeCitation
Indicates that an entity is associated with its standard or canonical citation form used as the primary reference.
-
B.
hasLegalEffect
Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
-
C.
isFormalizedBy
Indicates that something is given a defined, structured, or official form through a specific method, process, or representation.
-
D.
hasOfficialWrittenStandard
chosen
Indicates that there exists an officially recognized and codified written standard governing how something (e.g., a language or system) should be represented in writing.
-
E.
notableStandard
Indicates that one entity is a widely recognized or influential standard that the other entity is associated with or exemplifies.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5988708190aa86d9460cecf050 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.