Triple
T10483481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalenjin people |
E247230
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Bomet County |
E865568
|
NE 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: Bomet County | Statement: [Kalenjin people, region, Bomet County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bomet County Context triple: [Kalenjin people, region, Bomet County]
-
A.
Bomet County
chosen
Bomet County is an agricultural county in Kenya’s Rift Valley region, predominantly inhabited by the Kipsigis sub-group of the Kalenjin community.
-
B.
Nyeri County
Nyeri County is a highland region in central Kenya known for its fertile agricultural land, scenic views of Mount Kenya, and as the birthplace of Nobel Peace Prize laureate Wangari Maathai.
-
C.
Kisii County
Kisii County is an administrative county in southwestern Kenya known for its fertile highlands, intensive agriculture, and vibrant Kisii (Abagusii) community.
-
D.
Margibi County
Margibi County is an administrative region in central Liberia known for its agricultural activities and proximity to the capital, Monrovia.
-
E.
Kirinyaga County
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509678ac88190984f18a2162e2dcf |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc7fc0cc8190922b7b783d37f542 |
completed | April 10, 2026, 11:18 a.m. |
Created at: April 6, 2026, 12:22 p.m.