Triple
T29379735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministers of State of Uganda |
E745101
|
entity |
| Predicate | policyImplementationLevel |
P175252
|
FINISHED |
| Object | national and subnational levels within Uganda |
—
|
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: national and subnational levels within Uganda | Statement: [Ministers of State of Uganda, policyImplementationLevel, national and subnational levels within Uganda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyImplementationLevel Context triple: [Ministers of State of Uganda, policyImplementationLevel, national and subnational levels within Uganda]
-
A.
policyLevel
Indicates the degree or tier of strictness, scope, or priority associated with a given policy.
-
B.
policyImplication
Indicates that one policy, decision, or condition leads to, justifies, or necessitates another policy outcome or course of action.
-
C.
implementedPolicy
Indicates that a particular policy has been put into effect or carried out by an entity.
-
D.
mandateLevel
Indicates the degree or strictness of obligation imposed by a rule, policy, or authority on an action or relationship.
-
E.
policyElement
Indicates that something is a component or constituent part of a broader policy.
- 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cee3604c81908a07eade2f39064e |
completed | May 3, 2026, 4:28 a.m. |
Created at: April 28, 2026, 2:34 p.m.