Triple
T21073545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haut-Uélé Province |
E519171
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Isiro |
—
|
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: Isiro | Statement: [Haut-Uélé Province, capital, Isiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isiro Context triple: [Haut-Uélé Province, capital, Isiro]
-
A.
Isiro
chosen
Isiro is a city in the northeastern Democratic Republic of the Congo that serves as an important regional center for trade and administration.
-
B.
Bikoro
Bikoro is a town in the Équateur Province of the Democratic Republic of the Congo, known for being the focal point of a major Ebola virus disease outbreak in 2018.
-
C.
Mvele
Mvele is a Bantu language spoken by the Beti-Pahuin people in parts of Central Africa, particularly in Cameroon.
-
D.
Butembo
Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
-
E.
Abamakoro
Abamakoro is a small village located on the island of Nonouti in the Republic of Kiribati in the central Pacific Ocean.
- 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702d491a08190a9f5f28c0b72d38c |
completed | April 21, 2026, 4:53 a.m. |
Created at: April 16, 2026, 2:47 p.m.