Triple
T3754143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midlands State University |
E82003
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Gwanda |
E149377
|
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: Gwanda | Statement: [Midlands State University, hasCampusIn, Gwanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwanda Context triple: [Midlands State University, hasCampusIn, Gwanda]
-
A.
Gwanda
chosen
Gwanda is a small Zimbabwean town that serves as an administrative and commercial hub in the country’s arid south, known historically for cattle ranching and gold mining.
-
B.
Mufulira
Mufulira is a mining town in northern Zambia known for its large copper mines and role in the country's Copperbelt region.
-
C.
Bushenyi
Bushenyi is a town in western Uganda that serves as a regional hub and gateway to nearby attractions such as Queen Elizabeth National Park.
-
D.
Kalangala
Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
-
E.
Runyankole
Runyankole is a Bantu language spoken primarily by the Banyankole people in southwestern Uganda.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb94ffc08190a7fd1ce71a15f787 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f02fb680819092ea86040b4b5bcf |
completed | March 14, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:35 p.m.