Triple

T12792934
Position Surface form Disambiguated ID Type / Status
Subject Hartbeespoort Dam E305813 entity
Predicate nearTown P2064 FINISHED
Object Hartbeespoort E1067128 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: Hartbeespoort | Statement: [Hartbeespoort Dam, nearTown, Hartbeespoort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hartbeespoort
Context triple: [Hartbeespoort Dam, nearTown, Hartbeespoort]
  • A. Hartbeespoort chosen
    Hartbeespoort is a town and popular recreational area in North West Province, South Africa, known for its scenic setting around the Hartbeespoort Dam and views of the Magaliesberg mountains.
  • B. Tulbagh
    Tulbagh is a historic town in South Africa’s Western Cape, known for its Cape Dutch architecture and surrounding wine-producing valley.
  • C. Harrismith
    Harrismith is a town in the Free State province of South Africa, situated near the Drakensberg mountains and serving as an important transport and agricultural hub.
  • D. Rustenburg
    Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6b55248190ab938e69eb263612 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce5b2b988190892e14620fb87366 completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 5:30 p.m.