Triple
T21612429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anglican Church of Kenya |
E533344
|
entity |
| Predicate | hasDiocesesIn |
P1774
|
FINISHED |
| Object | Eldoret |
—
|
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: Eldoret | Statement: [Anglican Church of Kenya, hasDiocesesIn, Eldoret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eldoret Context triple: [Anglican Church of Kenya, hasDiocesesIn, Eldoret]
-
A.
Eldoret
chosen
Eldoret is a major town in western Kenya known as an agricultural and commercial hub and as a center for world-class long-distance runners.
-
B.
Kabete
Kabete is a prominent town in Kenya’s Central Region, situated within Kiambu County and known for its agricultural activity and proximity to Nairobi.
-
C.
Nakur
Nakur is a small town in the Saharanpur district of Uttar Pradesh, India, known for its local markets and role as a regional administrative and commercial center.
-
D.
Kapsabet
Kapsabet is a town in western Kenya known as an administrative and commercial center in a highland farming region and as a training base for elite long-distance runners.
-
E.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3ba79424819094e9ee93c4bbcc0b |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 16, 2026, 6:33 p.m.