Triple

T9078033
Position Surface form Disambiguated ID Type / Status
Subject Joel Stransky E217537 entity
Predicate placeOfBirth P1 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: [Joel Stransky, placeOfBirth, Pietermaritzburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pietermaritzburg
Context triple: [Joel Stransky, placeOfBirth, 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc95c7d3688190a4c1c6a92965eae4 completed April 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d017baebb881908cfecd3438a17166 completed April 3, 2026, 7:40 p.m.
Created at: March 30, 2026, 7:12 p.m.