Triple
T22658118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | كمال الشيخ |
E559285
|
entity |
| Predicate | مجال العمل |
P3
|
FINISHED |
| Object | السينما 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: السينما المصرية | Statement: [كمال الشيخ, مجال العمل, السينما المصرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مجال العمل Context triple: [كمال الشيخ, مجال العمل, السينما المصرية]
-
A.
employmentBasedCategory
Indicates that one entity’s classification or status is determined by its relationship to employment, such as being based on a specific job, role, or work-related category.
-
B.
employment
Indicates a relationship where one entity hires, contracts, or otherwise engages another to perform work or services, typically in exchange for compensation.
-
C.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
D.
fieldOfWork
chosen
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
E.
workFor
Indicates that one entity is employed by or performs work under the authority or direction 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765d10588190b4574f3e64617cd4 |
completed | April 29, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:07 p.m.