Triple

T6120418
Position Surface form Disambiguated ID Type / Status
Subject Yao E136467 entity
Predicate hasDialects P4251 FINISHED
Object Tanzania Yao E570025 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: Tanzania Yao | Statement: [Yao, hasDialects, Tanzania Yao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanzania Yao
Context triple: [Yao, hasDialects, Tanzania 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. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • C. Luba
    The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
  • D. Nyanja
    Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
  • E. Kaonde
    Kaonde is a Bantu language spoken primarily by the Kaonde people of northwestern Zambia and parts of the Democratic Republic of the Congo.
  • 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bef8dc08190b917ad7209188c62 completed March 22, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141619c148190b0fb94e2b1458510 completed March 23, 2026, 1:34 p.m.
Created at: March 22, 2026, 4:14 p.m.