Triple
T18635237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Mathuki |
E455528
|
entity |
| Predicate | nationality |
P2
|
FINISHED |
| Object | Kenyan |
—
|
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: Kenyan | Statement: [Peter Mathuki, nationality, Kenyan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenyan Context triple: [Peter Mathuki, nationality, Kenyan]
-
A.
Kenyan
chosen
Kenyan refers to a person from Kenya, an East African country known for its diverse cultures, languages, and rich history.
-
B.
Kenyan Luo
Kenyan Luo is a Nilotic ethnic group in western Kenya, primarily around Lake Victoria, known for its Dholuo language and rich cultural traditions in music, storytelling, and fishing.
-
C.
Gikuyu
Gikuyu is an alternative name for the Kikuyu, the largest ethnic group in Kenya known for their Bantu language and significant cultural and political influence in the country.
-
D.
Nandi–Kalenjin
Nandi–Kalenjin refers to the Kalenjin-speaking communities of Kenya, particularly associated with the Nandi subgroup known for their distinct cultural traditions and notable success in middle- and long-distance running.
-
E.
Kenya
Kenya is an East African country known for its diverse wildlife, scenic landscapes from savannas to highlands, and a coastline along the Indian Ocean.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc80b308190932303231524d372 |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 10, 2026, 11:46 a.m.