Triple
T22526921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | صراع في الوادي |
E556929
|
entity |
| Predicate | فئة |
P148517
|
FINISHED |
| Object | فيلم كلاسيكي مصري |
—
|
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: فيلم كلاسيكي مصري | Statement: [صراع في الوادي, فئة, فيلم كلاسيكي مصري]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: فئة Context triple: [صراع في الوادي, فئة, فيلم كلاسيكي مصري]
-
A.
faction
Indicates that an entity is formally affiliated with, or belongs to, a particular faction or organized group within a broader context.
-
B.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
C.
familyClass
Indicates that an entity belongs to, or is categorized within, a particular family grouping or class in a familial or taxonomic hierarchy.
-
D.
femaleFeature
Indicates that the subject possesses a characteristic or attribute that is typically associated with females.
-
E.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e8aa3b4c288190951cca06d42bea51 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:51 p.m.