Triple
T8880475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Kivu |
E211397
|
entity |
| Predicate | hasMajorPort |
P942
|
FINISHED |
| Object | Kibuye |
E573046
|
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: Kibuye | Statement: [Lake Kivu, hasMajorPort, Kibuye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kibuye Context triple: [Lake Kivu, hasMajorPort, Kibuye]
-
A.
Gisenyi
chosen
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.
-
B.
Butiama
Butiama is a village in northern Tanzania best known as the birthplace and hometown of the country’s founding president, Julius Nyerere.
-
C.
Nyabira
Nyabira is a small town in northern Zimbabwe located within Mashonaland West Province, serving as a local commercial and residential center.
-
D.
Butare
Butare is a city in southern Rwanda that became a significant site of massacres and atrocities during the 1994 Rwandan genocide.
-
E.
Kalangala
Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61677c9c8190aa09dc2a05d4cf95 |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc92c2f088190b953de2bfcbb5bb5 |
completed | April 3, 2026, 2:05 p.m. |
Created at: March 30, 2026, 6:52 p.m.