Triple

T22951338
Position Surface form Disambiguated ID Type / Status
Subject Malawi Yao E570025 entity
Predicate influencedBy P9 FINISHED
Object Chichewa 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: Chichewa | Statement: [Malawi Yao, influencedBy, Chichewa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chichewa
Context triple: [Malawi Yao, influencedBy, Chichewa]
  • A. Chichewa chosen
    Chichewa is a major Bantu language spoken primarily in Malawi and neighboring countries, serving as a national and widely used lingua franca in the region.
  • B. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • C. Shona
    Shona is a major Bantu language of Zimbabwe, widely spoken by the Shona people and used in education, media, and government.
  • D. Kimbundu
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • E. Swahili of the Congo
    Swahili of the Congo is a regional variety of Swahili spoken primarily in the Democratic Republic of the Congo, characterized by distinctive vocabulary and influences from local languages and colonial history.
  • 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_69e2459199d08190a8184ee2aa935842 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f181a285448190a718734fe933d51a completed April 29, 2026, 3:57 a.m.
Created at: April 17, 2026, 3:46 p.m.