Triple

T21804168
Position Surface form Disambiguated ID Type / Status
Subject Senzangakhona kaJama E538306 entity
Predicate predecessor P97 FINISHED
Object Jama kaNdaba 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: Jama kaNdaba | Statement: [Senzangakhona kaJama, predecessor, Jama kaNdaba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jama kaNdaba
Context triple: [Senzangakhona kaJama, predecessor, Jama kaNdaba]
  • A. Jama kaNdaba chosen
    Jama kaNdaba was an 18th-century Zulu king and clan leader, best known as the grandfather of the famous Zulu king Shaka.
  • B. Kijitonyama
    Kijitonyama is a residential and commercial neighborhood in Dar es Salaam, Tanzania, known as one of the urban wards within the Kinondoni District.
  • C. Kishambaa
    Kishambaa is an alternative name for the Shambala language, a Bantu language spoken primarily in northeastern Tanzania.
  • D. Kikamba-Doondo
    Kikamba-Doondo is a regional dialect of the Bantu language Kikongo, spoken by communities in parts of Central Africa.
  • E. Atandwa Kani
    Atandwa Kani is a South African actor known for his work in film, television, and theater, including roles in major international productions.
  • 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_69e0c4733f4081909a86622e7e6d15d2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0780126e88190a93dd8d0519eb8fc completed April 28, 2026, 9:04 a.m.
Created at: April 16, 2026, 6:53 p.m.