Triple

T1187823
Position Surface form Disambiguated ID Type / Status
Subject Southern Bantu E25286 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Lozi E50731 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: Lozi | Statement: [Southern Bantu, hasMemberLanguage, Lozi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lozi
Context triple: [Southern Bantu, hasMemberLanguage, Lozi]
  • A. Lozi chosen
    Lozi is a Bantu language spoken primarily by the Lozi people in western Zambia and surrounding regions of southern Africa.
  • B. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • C. Lokoja
    Lokoja is a city in central Nigeria located at the strategic confluence of the Niger and Benue rivers and serves as the capital of Kogi State.
  • D. Mandinka
    Mandinka is a major Mande language spoken primarily in The Gambia, Senegal, Guinea-Bissau, and neighboring West African countries by the Mandinka people.
  • E. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd568cf481908d10cf19a3ce28f3 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99775ca081909e4d8c81c40c277b completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:45 p.m.