Triple
T21053995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taita Taveta |
E518661
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Taveta |
—
|
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: Taveta | Statement: [Taita Taveta, hasMajorTown, Taveta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taveta Context triple: [Taita Taveta, hasMajorTown, Taveta]
-
A.
Taveta
chosen
Taveta is a key border town in southern Kenya near Tanzania, serving as an important regional trade and transport hub.
-
B.
Kajiado
Kajiado is a town in southern Kenya that serves as an administrative and commercial center for the surrounding Maasai-inhabited region.
-
C.
Marsabit
Marsabit is a remote market and administrative town in northern Kenya, known as a gateway to Marsabit National Park and its surrounding arid highlands.
-
D.
Mandera
Mandera is a remote town in northeastern Kenya near the borders with Somalia and Ethiopia, serving as a key regional trading and administrative center.
-
E.
Wazaramo
Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7e087c81908712ddc63e8b1e6c |
completed | April 21, 2026, 4:30 a.m. |
Created at: April 16, 2026, 2:36 p.m.