Triple
T25814512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | الجامعة الإسلامية بالمدينة المنورة |
E650210
|
entity |
| Predicate | تستقبل |
P4382
|
FINISHED |
| Object | طلاباً من قارات متعددة |
—
|
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 قارات متعددة | Statement: [الجامعة الإسلامية بالمدينة المنورة, تستقبل, طلاباً من قارات متعددة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تستقبل Context triple: [الجامعة الإسلامية بالمدينة المنورة, تستقبل, طلاباً من قارات متعددة]
-
A.
receives
chosen
Indicates that one entity is the recipient of something (such as an object, message, or action) from another entity.
-
B.
initialReception
Indicates the nature or quality of the first response or reaction something receives when it is introduced or presented.
-
C.
reception
Indicates the act of receiving or welcoming someone or something, often marking the initial acknowledgment or acceptance in an interaction or process.
-
D.
attendsTo
Indicates that one entity directs care, attention, or service toward another entity or task.
-
E.
takes
Indicates that one entity receives, accepts, or comes into 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.