Triple
T14796352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oyugis |
E347786
|
entity |
| Predicate | playsRoleInCounty |
P13451
|
FINISHED |
| Object | sub-county commercial hub |
—
|
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: sub-county commercial hub | Statement: [Oyugis, playsRoleInCounty, sub-county commercial hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsRoleInCounty Context triple: [Oyugis, playsRoleInCounty, sub-county commercial hub]
-
A.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
B.
associatedWithCounty
chosen
Indicates that an entity has a relationship or linkage to a specific county, such as jurisdiction, location, or administrative association.
-
C.
spokenInCounty
Indicates that a particular language or dialect is spoken within the geographic area of a specified county.
-
D.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
-
E.
hasCountySeatWithRole
Indicates that a county has a designated county seat that fulfills a specific administrative or governmental role.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.