Triple

T22951287
Position Surface form Disambiguated ID Type / Status
Subject Yao language E570024 entity
Predicate hasDialects P4251 FINISHED
Object Malawi Yao 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: Malawi Yao | Statement: [Yao language, hasDialects, Malawi Yao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malawi Yao
Context triple: [Yao language, hasDialects, Malawi Yao]
  • A. Malawi Yao chosen
    Malawi Yao is a regional variety of the Yao language spoken primarily in Malawi, distinguished by its own phonological and lexical features.
  • B. Mumbwa
    Mumbwa is a town in central Zambia known as an agricultural and mining hub west of the capital, Lusaka.
  • C. Lusambo
    Lusambo is a town in the Democratic Republic of the Congo that once served as an important colonial and regional administrative center in the Kasai area.
  • D. Malawi
    Malawi is a landlocked country in southeastern Africa known for Lake Malawi, its predominantly agricultural economy, and membership in regional and international organizations including the Commonwealth.
  • E. Silozi
    Silozi is a Bantu language spoken primarily by the Lozi people of western Zambia and surrounding regions.
  • 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.