Triple

T424516
Position Surface form Disambiguated ID Type / Status
Subject Niger–Congo languages E8177 entity
Predicate spokenIn P2266 FINISHED
Object Zimbabwe E1143 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: Zimbabwe | Statement: [Niger–Congo languages, spokenIn, Zimbabwe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zimbabwe
Context triple: [Niger–Congo languages, spokenIn, Zimbabwe]
  • A. Zimbabwe chosen
    Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
  • B. Zambia
    Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
  • C. Botswana
    Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
  • D. Eswatini
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • E. Mozambique
    Mozambique is a southeastern African nation on the Indian Ocean known for its Portuguese colonial heritage, rich cultural diversity, and extensive coastline with important ports and marine resources.
  • 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_69a2e7f1d1bc81909cf2dc9754a3c334 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eed3e4cc8190ba6aff3bd1adb06f completed Feb. 28, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4bec4b688190a2fcbff37b3dfe59 completed March 7, 2026, 4:01 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.