Triple
T22527007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | نهر الحب |
E556932
|
entity |
| Predicate | تصوير |
P17824
|
FINISHED |
| Object | وحدات تصوير داخلية في استوديوهات مصرية |
—
|
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: وحدات تصوير داخلية في استوديوهات مصرية | Statement: [نهر الحب, تصوير, وحدات تصوير داخلية في استوديوهات مصرية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تصوير Context triple: [نهر الحب, تصوير, وحدات تصوير داخلية في استوديوهات مصرية]
-
A.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
-
B.
photographyGenre
Indicates the specific genre or style of photography that characterizes a photographic work or activity.
-
C.
mediaDepictionAs
chosen
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
D.
visualMedium
Indicates that one entity serves as the visual medium or format through which another entity is presented, communicated, or experienced.
-
E.
studioFilm
Indicates that a film is produced, distributed, or otherwise created by a particular studio.
- 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.