Triple
T29420575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uganda Revenue Authority |
E746146
|
entity |
| Predicate | mainRegulatoryDomain |
P4800
|
FINISHED |
| Object | tax 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: tax law | Statement: [Uganda Revenue Authority, mainRegulatoryDomain, tax law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainRegulatoryDomain Context triple: [Uganda Revenue Authority, mainRegulatoryDomain, tax law]
-
A.
regulatoryDomain
chosen
Indicates that one entity defines or governs the rules, policies, or constraints under which another entity must operate.
-
B.
mainRegulatoryFunction
Indicates the primary regulatory role or control function that an entity performs within a system, process, or framework.
-
C.
mainRegulatoryObjective
Indicates the primary regulatory goal or purpose that guides and justifies a regulator’s actions or framework.
-
D.
regulatoryField
Indicates that one entity operates within, is governed by, or is associated with a particular area or domain of regulation defined by another entity.
-
E.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
- 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66a68fedc8190ab94d22edc6ff90b |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:05 p.m.