Triple
T7073783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Lusaka |
E164763
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Lusaka |
E31817
|
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: Lusaka | Statement: [University of Lusaka, locatedIn, Lusaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lusaka Context triple: [University of Lusaka, locatedIn, Lusaka]
-
A.
Lusaka, Zambia
chosen
Lusaka, Zambia is the capital and largest city of Zambia, serving as the country’s political, economic, and cultural center.
-
B.
Lilongwe
Lilongwe is the largest city and administrative and political center of Malawi, located in the country’s central region.
-
C.
Matadi
Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
-
D.
Lubumbashi
Lubumbashi is the second-largest city in the Democratic Republic of the Congo and a major mining and commercial center in the southeastern part of the country.
-
E.
Kasane
Kasane is a small town in northern Botswana that serves as a key gateway and service hub for visitors to Chobe National Park and the surrounding wildlife areas.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4ccb42c81909f5627aa97db7a84 |
completed | March 27, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8682696a48190aec021bd00c6f633 |
completed | March 28, 2026, 11:45 p.m. |
Created at: March 27, 2026, 2:39 p.m.