Triple
T8880488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Kivu |
E211397
|
entity |
| Predicate | borderCity |
P15361
|
FINISHED |
| Object | Gisenyi |
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: Gisenyi | Statement: [Lake Kivu, borderCity, Gisenyi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gisenyi Context triple: [Lake Kivu, borderCity, Gisenyi]
-
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.
Bukavu
Bukavu is a major city in the eastern Democratic Republic of the Congo, located on the southwestern shore of Lake Kivu near the Rwandan border.
-
C.
Butare
Butare is a city in southern Rwanda that became a significant site of massacres and atrocities during the 1994 Rwandan genocide.
-
D.
Bujumbura
Bujumbura is the largest city and former capital of Burundi, located on the northeastern shore of Lake Tanganyika.
-
E.
Nsanje
Nsanje is a town in southern Malawi near the border with Mozambique, known as a key transport and trading center in the Lower Shire Valley.
- 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_69cfdb8094a88190a88e3f23f9ae17c7 |
completed | April 3, 2026, 3:23 p.m. |
Created at: March 30, 2026, 6:52 p.m.