Triple
T23299214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyeri County |
E590255
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Embu 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: Embu County | Statement: [Nyeri County, borders, Embu County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Embu County Context triple: [Nyeri County, borders, Embu County]
-
A.
Embu County
chosen
Embu County is an administrative region in eastern Kenya, located on the southeastern slopes of Mount Kenya and inhabited predominantly by the Embu people.
-
B.
Nandi County
Nandi County is a highland county in Kenya’s Rift Valley region, known as a stronghold of the Kalenjin community and for producing many of the country’s elite long-distance runners.
-
C.
Wanju County
Wanju County is a largely rural administrative region in South Korea known for its agriculture and proximity to the city of Jeonju.
-
D.
Siaya County
Siaya County is an administrative county in western Kenya, located along the shores of Lake Victoria and known as the birthplace of several prominent Kenyan political figures.
-
E.
Makueni County
Makueni County is a semi-arid administrative region in southeastern Kenya known for its agriculture, water-scarcity challenges, and location along key transport and river basins.
- 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.