Triple
T19790484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Line (Tanzania) |
E475395
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Kigoma |
—
|
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: Kigoma | Statement: [Central Line (Tanzania), terminus, Kigoma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kigoma Context triple: [Central Line (Tanzania), terminus, Kigoma]
-
A.
Kigoma
chosen
Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
-
B.
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.
-
C.
Gikondo
Gikondo is an urban sector of Kigali, Rwanda, known for its industrial area and proximity to the city center.
-
D.
Nyamwezi
Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
-
E.
Mbulu
Mbulu is a local name for the Congo peafowl, a rare and elusive forest-dwelling bird species native to the Congo Basin in Central Africa.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c217bc819092c517b27ca22087 |
completed | April 20, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:49 p.m.