Triple
T16653313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Longonot |
E404661
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Naivasha |
E381720
|
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: Naivasha | Statement: [Mount Longonot, locatedNear, Naivasha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naivasha Context triple: [Mount Longonot, locatedNear, Naivasha]
-
A.
Naivasha
chosen
Naivasha is a town in Kenya’s Rift Valley region known as a gateway to the nearby Lake Naivasha and surrounding wildlife and flower-farming areas.
-
B.
Lake Naivasha
Lake Naivasha is a freshwater lake in Kenya’s Great Rift Valley, renowned for its rich birdlife, hippo populations, and surrounding flower farms and wildlife conservancies.
-
C.
Nanyuki
Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
-
D.
Nyamira
Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
-
E.
Albert Nyanza
Albert Nyanza is a large African Great Lake located on the border between Uganda and the Democratic Republic of the Congo, forming part of the upper Nile River system.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bf861348190b2b0b5574d4ddb4f |
completed | April 18, 2026, 12:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084c4c6a08190874264b2840fc70d |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:18 a.m.