Triple

T14417207
Position Surface form Disambiguated ID Type / Status
Subject Northern Mozambique E357483 entity
Predicate languageSpoken P151 FINISHED
Object Makonde language E1083821 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: Makonde language | Statement: [Northern Mozambique, languageSpoken, Makonde language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makonde language
Context triple: [Northern Mozambique, languageSpoken, Makonde language]
  • A. Makonde language chosen
    The Makonde language is a Bantu language spoken primarily by the Makonde people of northern Mozambique and southern Tanzania.
  • B. Kaonde language
    The Kaonde language is a Bantu language spoken primarily by the Kaonde people of northwestern Zambia and parts of the Democratic Republic of the Congo.
  • C. Ngindo language
    The Ngindo language is a Bantu language spoken by the Ngindo people of southeastern Tanzania.
  • D. Mbunda language
    The Mbunda language is a Bantu language spoken primarily by the Mbunda people in parts of Angola and Zambia.
  • E. Konongo language
    The Konongo language is a Bantu language of East Africa, closely related to Sukuma and spoken by the Konongo people.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90cec8e4819087c72d82f9caacda completed April 14, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd552bc32c81908a562732e3950442 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.