Triple
T21175430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kwale County |
E521798
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Kwale |
—
|
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: Kwale | Statement: [Kwale County, hasCapital, Kwale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kwale Context triple: [Kwale County, hasCapital, Kwale]
-
A.
Kwale
chosen
Kwale is a small town in southeastern Kenya that serves as the administrative headquarters of Kwale County near the Indian Ocean coast.
-
B.
Kwale
Kwale is a prominent town in Nigeria’s Delta State, recognized as one of the key urban centers of the Anioma (Igbo-speaking) region.
-
C.
Kasangulu
Kasangulu is a town and transport hub in western Democratic Republic of the Congo, located near Kinshasa and known for its position along key road and rail routes.
-
D.
Mbau
Mbau is a town in the Beni Territory of North Kivu Province in the eastern Democratic Republic of the Congo, known for its location in a region affected by conflict and insecurity.
-
E.
Unawatuna
Unawatuna is a popular coastal town in southern Sri Lanka known for its palm-fringed beach, coral-rich bay, and laid-back tourist atmosphere.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7271597288190b04baff9ca8d866c |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 3 p.m.