Triple
T26172811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عبد القادر الجيلاني |
E654453
|
entity |
| Predicate | الموضوعات التي درّسها |
P98445
|
FINISHED |
| Object | التزكية والسلوك |
—
|
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: التزكية والسلوك | Statement: [عبد القادر الجيلاني, الموضوعات التي درّسها, التزكية والسلوك]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الموضوعات التي درّسها Context triple: [عبد القادر الجيلاني, الموضوعات التي درّسها, التزكية والسلوك]
-
A.
typicalCourseTopic
Indicates that a given topic is commonly or characteristically covered as part of a particular course.
-
B.
teachingSubject
chosen
Indicates that an entity is engaged in teaching or instructing another entity in a particular subject or field of knowledge.
-
C.
taughtCourse
Indicates that an entity (typically an instructor) has taught a particular course.
-
D.
materiasQueConocen
Indicates a relationship where certain subjects or topics are known or mastered by specific entities.
-
E.
taughtThat
Indicates that one entity provided instruction or education to another entity about a specific subject, skill, or concept.
- 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_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 8:36 p.m.