Triple
T23299211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyeri County |
E590255
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Kirinyaga County |
—
|
NE NERFINISHED |
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: Kirinyaga County | Statement: [Nyeri County, borders, Kirinyaga County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirinyaga County Context triple: [Nyeri County, borders, Kirinyaga County]
-
A.
Kirinyaga County
chosen
Kirinyaga County is an administrative region in central Kenya known for its fertile agricultural land on the slopes of Mount Kenya and its production of tea, coffee, and horticultural crops.
-
B.
Nyandarua County
Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
-
C.
Laikipia County
Laikipia County is a region in central Kenya known for its wildlife conservancies, ranches, and growing tourism and agricultural sectors.
-
D.
Nyamira County
Nyamira County is an administrative county in western Kenya known for its predominantly Kisii community, hilly highland terrain, and tea and coffee farming.
-
E.
Nakuru County
Nakuru County is a region in Kenya’s Rift Valley known for its lakes, wildlife, and agricultural activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d133448190bf350a9f51c1531c |
completed | April 29, 2026, 5:27 a.m. |
Created at: April 17, 2026, 5:03 p.m.