Triple
T8941308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moses Wetang'ula |
E212905
|
entity |
| Predicate | legalLicense |
P74872
|
FINISHED |
| Object | admitted to the Kenyan Bar |
—
|
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: admitted to the Kenyan Bar | Statement: [Moses Wetang'ula, legalLicense, admitted to the Kenyan Bar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalLicense Context triple: [Moses Wetang'ula, legalLicense, admitted to the Kenyan Bar]
-
A.
legalLicenseIn
chosen
Indicates that an entity holds a valid legal license or authorization to operate, practice, or conduct a specified activity within a particular jurisdiction or region.
-
B.
licenseFocus
Indicates that a license specifically targets, applies to, or is primarily concerned with a particular subject, activity, or scope.
-
C.
license
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
D.
licenseFor
Indicates that one entity grants or holds formal permission or authorization for another entity to perform an activity, use a resource, or operate under specified conditions.
-
E.
licenseAdvocated
Indicates that an agent publicly supports, recommends, or argues in favor of a particular license being used or adopted.
- 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b9c14c8190b80c3df0cdba2747 |
completed | April 1, 2026, 12:28 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:58 p.m.