Triple
T313818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kampala Amendments |
E7663
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Kampala |
E40695
|
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: Kampala | Statement: [Kampala Amendments, namedAfter, Kampala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kampala Context triple: [Kampala Amendments, namedAfter, Kampala]
-
A.
Kampala
chosen
Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
-
B.
Nairobi
Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
-
C.
Masvingo
Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
-
D.
Uganda
Uganda is a landlocked country in East Africa known for its diverse landscapes, abundant wildlife, and location along the equator.
-
E.
Lusaka, Zambia
Lusaka, Zambia is the capital and largest city of Zambia, serving as the country’s political, economic, and cultural center.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea4bd6a081909bdb57602c7093b4 |
completed | Feb. 28, 2026, 1:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3c8b7274881908e13da8bb2c83858 |
completed | March 1, 2026, 5:03 a.m. |
Created at: Feb. 28, 2026, 1:07 p.m.