Triple
T3964444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Zimbabwe University |
E85981
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Masvingo |
E11625
|
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: Masvingo | Statement: [Great Zimbabwe University, locatedIn, Masvingo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masvingo Context triple: [Great Zimbabwe University, locatedIn, Masvingo]
-
A.
Masvingo
chosen
Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
-
B.
Harare
Harare is the largest city and main economic, political, and cultural center of Zimbabwe.
-
C.
Mutare
Mutare is a major city in eastern Zimbabwe, serving as the capital of Manicaland Province and an important commercial and transport hub near the border with Mozambique.
-
D.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
-
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_69aed93a96908190bcbdbfa718f155bd |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef97326888190bbfe15b218e3112e |
completed | March 9, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a831b0408190a0862803844d779d |
completed | March 14, 2026, 6:25 p.m. |
Created at: March 9, 2026, 3:31 p.m.