Triple
T20627911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kampala–Jinja Highway |
E506868
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Lugazi |
—
|
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: Lugazi | Statement: [Kampala–Jinja Highway, passesNear, Lugazi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lugazi Context triple: [Kampala–Jinja Highway, passesNear, Lugazi]
-
A.
Lugazi
chosen
Lugazi is a town in central Uganda known for its sugar plantations and location along the Kampala–Jinja highway.
-
B.
Lusoga
Lusoga is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
-
C.
Lusamia
Lusamia is a Bantu language spoken by the Samia people living around the Kenya–Uganda border region in East Africa.
-
D.
Kalambo
Kalambo is an agricultural research station site in the Lake Tanganyika region of Tanzania, known for supporting tropical crop and farming systems research.
-
E.
Kazungula
Kazungula is a border town in southern Africa, strategically located near the Zambezi River where Botswana, Zambia, Zimbabwe, and Namibia meet, and known for its important regional transport links.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe645888190b639ebedc5b3041a |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.