Triple
T1030762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimvita |
E22244
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Mombasa County |
E47207
|
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: Mombasa County | Statement: [Kimvita, spokenIn, Mombasa County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mombasa County Context triple: [Kimvita, spokenIn, Mombasa County]
-
A.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
-
B.
Nakuru
Nakuru is a prominent Kenyan city in the Rift Valley region, known for its proximity to Lake Nakuru National Park and its role as an important agricultural and commercial center.
-
C.
Mombasa
chosen
Mombasa is a major coastal city in Kenya known as a key regional port and historic trading hub on the Indian Ocean.
-
D.
Kilimanjaro Region
Kilimanjaro Region is an administrative area in northeastern Tanzania best known for encompassing Africa’s highest peak, Mount Kilimanjaro, and serving as a major hub for tourism and agriculture.
-
E.
Kigoma Region
Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b810429081908a97014ca740824b |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bbf5a1c819086e1ff529d05f311 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.