Triple

T11924752
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Matabele E283750 entity
Predicate founder P104 FINISHED
Object Mzilikazi E550545 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: Mzilikazi | Statement: [Kingdom of Matabele, founder, Mzilikazi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mzilikazi
Context triple: [Kingdom of Matabele, founder, Mzilikazi]
  • A. Mzilikazi chosen
    Mzilikazi was a 19th-century Southern African king who founded the Ndebele (Matabele) nation and led its migration to what is now Zimbabwe.
  • B. Mthwakazi
    Mthwakazi is a historic Ndebele kingdom in southwestern Zimbabwe, often associated with the precolonial state founded by King Mzilikazi in the 19th century.
  • C. Zindziswa
    Zindziswa is the given first name of Zindzi Mandela, the South African diplomat, poet, and daughter of Nelson Mandela and Winnie Madikizela-Mandela.
  • D. Makaziwe
    Makaziwe is a South African academic and businesswoman best known as the daughter of Nelson Mandela.
  • E. Mabalako
    Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8e2fc648190a446c1917db1c7d9 completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f45891f9c081909250a0aa0f7448d2 completed May 1, 2026, 7:38 a.m.
Created at: April 8, 2026, 9:45 p.m.