Triple

T22115999
Position Surface form Disambiguated ID Type / Status
Subject High Courts of South Africa E546542 entity
Predicate hasSeatIn P3522 FINISHED
Object Makhanda 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: Makhanda | Statement: [High Courts of South Africa, hasSeatIn, Makhanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makhanda
Context triple: [High Courts of South Africa, hasSeatIn, Makhanda]
  • A. Makhanda chosen
    Makhanda is a historic city in South Africa’s Eastern Cape, known as a major educational and cultural center and home to Rhodes University and the National Arts Festival.
  • B. Sandile kaNgqika
    Sandile kaNgqika was a prominent 19th-century Xhosa chief and military leader who played a central role in resisting British colonial expansion in the Eastern Cape.
  • C. Thabo
    Thabo is a common Southern African given name, often used in countries such as South Africa and Lesotho.
  • D. Thembekile
    Thembekile is a given name notably borne by Thembekile Mandela, one of Nelson Mandela’s sons.
  • E. Mangosuthu
    Mangosuthu is the given name of Mangosuthu Buthelezi, a prominent South African Zulu prince and political leader.
  • 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_69e11e38b3848190ac3a4fa97d56e65a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1294dc1148190b95ff00f475a6713 completed April 28, 2026, 9:40 p.m.
Created at: April 16, 2026, 8:31 p.m.