Triple
T10480162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | مستقبل وطن |
E247148
|
entity |
| Predicate | القطاع |
P71
|
FINISHED |
| Object | القطاع السياسي |
—
|
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: القطاع السياسي | Statement: [مستقبل وطن, القطاع, القطاع السياسي]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: القطاع Context triple: [مستقبل وطن, القطاع, القطاع السياسي]
-
A.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
B.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
C.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
D.
sectorBase
Indicates that one entity serves as the primary base or foundational location for operations within a particular sector of another entity.
-
E.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5095b2ec881909e1220d83e750a75 |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:22 p.m.