Triple
T30481325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | آل سعود |
E775594
|
entity |
| Predicate | تأثيرها الإقليمي |
P19397
|
FINISHED |
| Object | الشرق الأوسط |
—
|
NE NERFINISHED |
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: الشرق الأوسط | Statement: [آل سعود, تأثيرها الإقليمي, الشرق الأوسط]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تأثيرها الإقليمي Context triple: [آل سعود, تأثيرها الإقليمي, الشرق الأوسط]
-
A.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
B.
influencesRegion
chosen
Indicates that one entity has an effect on, shapes, or alters the conditions, characteristics, or behavior of a specified region.
-
C.
hasRegionalInfluenceFrom
Indicates that one entity’s influence, impact, or authority in a region is derived from or shaped by another entity.
-
D.
geographicalEffect
Indicates how one geographical feature, condition, or event influences or alters another in terms of physical, environmental, or spatial characteristics.
-
E.
regionOfCulturalImpact
Indicates the geographic area where an entity’s cultural influence, activities, or effects are most significantly felt or observed.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f687415610819081818d08f7c79a81 |
completed | May 2, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:12 p.m.