Triple
T19967294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunyani River |
E479970
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Chinhoyi |
—
|
NE NERFINISHED |
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: Chinhoyi | Statement: [Hunyani River, passesNear, Chinhoyi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chinhoyi Context triple: [Hunyani River, passesNear, Chinhoyi]
-
A.
Chinhoyi
chosen
Chinhoyi is a town in northern Zimbabwe known as an administrative center and for the nearby Chinhoyi Caves.
-
B.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
-
C.
Cedza
Cedza is a Swazi prince and social entrepreneur known for his work in youth leadership and development initiatives.
-
D.
Chivhu, Zimbabwe
Chivhu, Zimbabwe is a small town in central Zimbabwe known as an agricultural center and one of the country’s oldest European-settled communities.
-
E.
Chegutu
Chegutu is a town in central northern Zimbabwe known for its agricultural activities and gold mining.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc5e41881908c1e8867820f1c0c |
completed | April 20, 2026, 5 p.m. |
Created at: April 10, 2026, 1:54 p.m.