Triple
T25814488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الجامعة الإسلامية بالمدينة المنورة |
E650210
|
entity |
| Predicate | تستقطب |
P1347
|
FINISHED |
| Object | طلاباً من مختلف دول العالم |
—
|
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: طلاباً من مختلف دول العالم | Statement: [الجامعة الإسلامية بالمدينة المنورة, تستقطب, طلاباً من مختلف دول العالم]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تستقطب Context triple: [الجامعة الإسلامية بالمدينة المنورة, تستقطب, طلاباً من مختلف دول العالم]
-
A.
attracts
chosen
Indicates that one entity exerts a force or influence that draws another entity toward it.
-
B.
اعتنق
Indicates adopting or embracing a belief, religion, or doctrine as one’s own.
-
C.
يراقب
Indicates that one entity is watching, monitoring, or observing another entity or situation.
-
D.
التأثير
Indicates a relationship where one entity produces a change or has an influence on another entity or its state.
-
E.
aimsToCapture
Indicates an intention or effort by one entity to take control of, seize, or gain possession of another entity.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f600c84ac4819091492e52a5a8b873 |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 7:12 a.m.