Triple
T14667107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Province |
E344406
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Kapiri Mposhi |
E637652
|
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: Kapiri Mposhi | Statement: [Central Province, hasTown, Kapiri Mposhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapiri Mposhi Context triple: [Central Province, hasTown, Kapiri Mposhi]
-
A.
Kapiri Mposhi
chosen
Kapiri Mposhi is a town in central Zambia that serves as a key rail and road junction linking the country to Tanzania and other regions.
-
B.
Chegutu
Chegutu is a town in central northern Zimbabwe known for its agricultural activities and gold mining.
-
C.
Marondera
Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
-
D.
Manzini
Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
-
E.
Luanshya
Luanshya is a mining town in Zambia known for its copper production and role in the country’s Copperbelt region.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54dda1c8190bf16d17e26a2bba6 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cdc54a881909d9ea43c26b9d5ef |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:27 a.m.