Triple
T22527295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | أحمد مظهر |
E556939
|
entity |
| Predicate | خلفية_عسكرية |
P38925
|
FINISHED |
| Object | تخرج في الكلية الحربية المصرية |
—
|
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: تخرج في الكلية الحربية المصرية | Statement: [أحمد مظهر, خلفية_عسكرية, تخرج في الكلية الحربية المصرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: خلفية_عسكرية Context triple: [أحمد مظهر, خلفية_عسكرية, تخرج في الكلية الحربية المصرية]
-
A.
militaryBackground
chosen
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
B.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
C.
countryMilitary
Indicates that a country possesses, controls, or is associated with a particular military force or armed organization.
-
D.
militaryBacked
Indicates that one entity is supported, protected, or sustained by the military power or armed forces of another entity.
-
E.
militaryHistoryTopic
Indicates that there exists a relationship where the subject is a topic, theme, or subject matter specifically concerned with military history.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed411488190a51320930b9805c2 |
completed | April 29, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.