Triple
T22675803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kivu region |
E560341
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Uvira |
—
|
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: Uvira | Statement: [Kivu region, hasCity, Uvira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uvira Context triple: [Kivu region, hasCity, Uvira]
-
A.
Uvira
chosen
Uvira is a city in the eastern Democratic Republic of the Congo, located on the northern shores of Lake Tanganyika near the border with Burundi.
-
B.
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.
-
C.
Bukoba
Bukoba is a town on the western shore of Lake Victoria in northwestern Tanzania, serving as the capital of the Kagera Region and a local transport and trade hub.
-
D.
Gisenyi
Gisenyi is a city in northwestern Rwanda on the shores of Lake Kivu, historically significant as one of the key sites affected during the 1994 Rwandan genocide.
-
E.
Butare
Butare is a city in southern Rwanda that became a significant site of massacres and atrocities during the 1994 Rwandan genocide.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17823bd1881908958b0a8ba59e199 |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 17, 2026, 3:11 p.m.