Triple
T1308151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matabeleland South |
E27927
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Zimbabwe |
E1143
|
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: Zimbabwe | Statement: [Matabeleland South, partOf, Zimbabwe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zimbabwe Context triple: [Matabeleland South, partOf, Zimbabwe]
-
A.
Zimbabwe
chosen
Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
-
B.
Botswana and Zimbabwe
Botswana and Zimbabwe are neighboring landlocked countries in Southern Africa that share close historical, economic, and ecological ties.
-
C.
Zambia
Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
-
D.
Botswana
Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
-
E.
Eswatini
Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c13806b48190a0db33f8e5d53734 |
completed | March 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fa73fe8819097bcd6c07793bc52 |
completed | March 9, 2026, 1:17 a.m. |
Created at: March 1, 2026, 7:51 p.m.