Triple
T11110133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Matfield |
E262732
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Polokwane |
E124879
|
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: Polokwane | Statement: [Victor Matfield, placeOfBirth, Polokwane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Polokwane Context triple: [Victor Matfield, placeOfBirth, Polokwane]
-
A.
Polokwane
chosen
Polokwane is a city in South Africa’s Limpopo province that served as one of the venues for matches during the 2010 FIFA World Cup.
-
B.
Mthatha
Mthatha is a town in South Africa known as a regional economic and administrative center in the Eastern Cape and as the birthplace of Nelson Mandela.
-
C.
Mbombela
Mbombela is a city in northeastern South Africa that serves as a regional economic and administrative hub near the border with Mozambique.
-
D.
Mogoditshane
Mogoditshane is a rapidly growing suburban township located just outside Botswana’s capital, Gaborone.
-
E.
Tzaneen
Tzaneen is a large agricultural town in South Africa’s Limpopo province, known for its subtropical climate and extensive fruit farming.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a6964508190b679303d3b3a4fd6 |
completed | April 9, 2026, 12:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d759bc88190b670c373f3647a41 |
completed | April 19, 2026, 1:18 a.m. |
Created at: April 8, 2026, 9:27 p.m.