Triple
T36311537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenya Vision 2030 |
E894079
|
entity |
| Predicate | politicalPillarFocus |
P25878
|
FINISHED |
| Object | rule of law |
—
|
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: rule of law | Statement: [Kenya Vision 2030, politicalPillarFocus, rule of law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalPillarFocus Context triple: [Kenya Vision 2030, politicalPillarFocus, rule of law]
-
A.
isPoliticalHub
Indicates that a place or entity serves as a central location or focal point for political activity, organization, or influence.
-
B.
politicalIssueFor
chosen
Indicates a relationship where a particular topic, problem, or policy area is considered a matter of political concern or debate for a given entity.
-
C.
politicalIssueIn
Indicates that a political issue is relevant to, occurs within, or is associated with a particular geographic or political region.
-
D.
politicalCategory
Indicates the political classification or ideological grouping that an entity belongs to or is associated with.
-
E.
politicalInterest
Indicates that an entity has an interest, concern, or engagement in political matters, issues, or activities.
- 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_69fef2db323c8190821bda53f22a42be |
completed | May 9, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69fef21d63c88190abf6a99b59b3c655 |
completed | May 9, 2026, 8:36 a.m. |
Created at: May 3, 2026, 4:09 p.m.