Triple
T23038277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Botshabelo |
E573666
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | Thaba Nchu |
—
|
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: Thaba Nchu | Statement: [Botshabelo, nearbySettlement, Thaba Nchu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thaba Nchu Context triple: [Botshabelo, nearbySettlement, Thaba Nchu]
-
A.
Thaba Nchu
chosen
Thaba Nchu is a town in South Africa’s Free State province, historically a Tswana settlement and now a satellite town of Bloemfontein.
-
B.
Thohoyandou
Thohoyandou is a town in South Africa’s Limpopo province that serves as an administrative, commercial, and educational hub for the surrounding region.
-
C.
Matsapha
Matsapha is an industrial town in central Eswatini known for its manufacturing hub and proximity to the city of Manzini.
-
D.
Thabazimbi
Thabazimbi is a small mining town in South Africa’s Limpopo province, known for its iron ore industry and proximity to the scenic Marakele National Park.
-
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 (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_69e245b911188190bc3d96326c847969 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f185111f0881908991fcd6cdc7db9f |
completed | April 29, 2026, 4:12 a.m. |
Created at: April 17, 2026, 3:53 p.m.