Triple
T36311544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenya Vision 2030 |
E894079
|
entity |
| Predicate | economicPillarFocus |
P2313
|
FINISHED |
| Object | wealth creation |
—
|
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: wealth creation | Statement: [Kenya Vision 2030, economicPillarFocus, wealth creation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicPillarFocus Context triple: [Kenya Vision 2030, economicPillarFocus, wealth creation]
-
A.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
B.
economicScope
Indicates the range or extent of economic activities, impacts, or considerations that a given entity, action, or relationship encompasses.
-
C.
economicSectorSourceOfWealth
Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
-
D.
economicSpeciality
Indicates a relationship where an entity is characterized by, or primarily engaged in, a particular economic field, sector, or type of economic activity.
-
E.
economicAspect
chosen
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:09 p.m.