Triple
T9229608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maritzburg College |
E221781
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Pietermaritzburg |
E42615
|
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: Pietermaritzburg | Statement: [Maritzburg College, city, Pietermaritzburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pietermaritzburg Context triple: [Maritzburg College, city, Pietermaritzburg]
-
A.
Pietermaritzburg
chosen
Pietermaritzburg is a major city in South Africa’s KwaZulu-Natal province, historically significant as a colonial administrative center and now known for its Victorian architecture and role as a regional economic and educational hub.
-
B.
Grahamstown
Grahamstown is a historic university town in South Africa, renowned for its colonial-era architecture and the annual National Arts Festival.
-
C.
Pietersburg
Pietersburg is the former name of Polokwane, a major city and administrative center in South Africa’s Limpopo province.
-
D.
Durban
Durban is a major coastal city in South Africa known for its busy port, subtropical climate, and significant Indian community.
-
E.
Uitenhage
Uitenhage is a South African town in the Eastern Cape known historically for its automotive industry and as part of the greater Port Elizabeth (Gqeberha) urban area.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccdaa1c5b4819081dac6713053a8ae |
completed | April 1, 2026, 8:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c3f31db48190a63d0d60f108496f |
completed | April 5, 2026, 2:07 a.m. |
Created at: March 30, 2026, 7:29 p.m.