Triple
T11921614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiryandongo District |
E283669
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Kiryandongo |
E957690
|
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: Kiryandongo | Statement: [Kiryandongo District, administrativeCenter, Kiryandongo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiryandongo Context triple: [Kiryandongo District, administrativeCenter, Kiryandongo]
-
A.
Kiryandongo
chosen
Kiryandongo is a town in western Uganda that serves as the administrative and commercial center of Kiryandongo District.
-
B.
Bunyoro
Bunyoro is a traditional kingdom and historical region in western Uganda that was once a powerful pre-colonial African state.
-
C.
Nimule
Nimule is a South Sudanese border town near Uganda that serves as a key trade and transport hub in the region.
-
D.
Gokwe
Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
-
E.
Owendo
Owendo is a port city in western Gabon that serves as an important industrial and maritime hub near the capital, Libreville.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8e1b08481909ed291667035f330 |
completed | April 10, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48a61e120819089e44568ce7e99fe |
completed | May 1, 2026, 11:11 a.m. |
Created at: April 8, 2026, 9:45 p.m.