Triple
T15985468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakuru County |
E387680
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Narok County |
E318871
|
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: Narok County | Statement: [Nakuru County, borders, Narok County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narok County Context triple: [Nakuru County, borders, Narok County]
-
A.
Narok County
chosen
Narok County is a county in southwestern Kenya known for its vast savannah landscapes, rich Maasai culture, and world-famous wildlife tourism.
-
B.
Nakuru County
Nakuru County is a region in Kenya’s Rift Valley known for its lakes, wildlife, and agricultural activities.
-
C.
Nyandarua County
Nyandarua County is an administrative region in central Kenya known for its highland agriculture and proximity to the Aberdare Range.
-
D.
Baringo County
Baringo County is a largely rural county in Kenya’s Rift Valley region, known for its lakes, diverse ethnic communities, and semi-arid landscapes.
-
E.
Isiolo County
Isiolo County is an arid, sparsely populated administrative region in northern Kenya known for its pastoralist communities, wildlife conservancies, and strategic position as a transport and trade hub.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157589d78819091f7b9b1081dd6ad |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfb95b348190a006f699c01e85ce |
completed | May 10, 2026, 6:34 p.m. |
Created at: April 10, 2026, 4:54 a.m.