Triple
T26172808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عبد القادر الجيلاني |
E654453
|
entity |
| Predicate | اللغة المستخدمة في التعليم |
P36232
|
FINISHED |
| Object | العربية |
—
|
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: العربية | Statement: [عبد القادر الجيلاني, اللغة المستخدمة في التعليم, العربية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: اللغة المستخدمة في التعليم Context triple: [عبد القادر الجيلاني, اللغة المستخدمة في التعليم, العربية]
-
A.
alsoUsesLanguageOfInstruction
Indicates that an entity, in addition to its primary language, uses the same language that is designated as the language of instruction in a given context.
-
B.
languageOfTeachings
chosen
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
C.
usedInEducationIn
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
D.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
E.
educationUse
Indicates the use or application of something specifically for educational purposes or in an educational context.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60c4485748190aff17798bca51406 |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 8:36 p.m.