Triple
T10490528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luo language |
E247405
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object | Kisumu Luo |
E43852
|
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: Kisumu Luo | Statement: [Luo language, hasDialects, Kisumu Luo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kisumu Luo Context triple: [Luo language, hasDialects, Kisumu Luo]
-
A.
Rakai Kayuwangi
Rakai Kayuwangi was a ruler of the Mataram Kingdom in Central Java, known from Old Javanese inscriptions as one of the early monarchs in the Medang (Mataram) dynasty.
-
B.
Kisumu
chosen
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
-
C.
Wazaramo
Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
-
D.
Rutooro
Rutooro is a Bantu language spoken primarily by the Tooro people in western Uganda.
-
E.
Kisii
Kisii is a bustling commercial and administrative town in southwestern Kenya, serving as a key hub for the surrounding agricultural highlands and the Kisii community.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097d61e08190952d4354ef1bce52 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc9792308190b09d6aaed63dd418 |
completed | April 10, 2026, 11:18 a.m. |
Created at: April 6, 2026, 12:23 p.m.