Triple

T2533994
Position Surface form Disambiguated ID Type / Status
Subject Atlantic–Congo languages E56225 entity
Predicate includesLanguage P2177 FINISHED
Object Bemba E184650 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: Bemba | Statement: [Atlantic–Congo languages, includesLanguage, Bemba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bemba
Context triple: [Atlantic–Congo languages, includesLanguage, Bemba]
  • A. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • B. Bemba people chosen
    The Bemba people are a major Bantu ethnic group of central and northern Zambia, known for their matrilineal social structure, rich oral traditions, and historical Bemba Kingdom.
  • C. Ngoni
    Ngoni is a Bantu language spoken by the Ngoni people of parts of Malawi, Tanzania, Mozambique, and Zambia, reflecting historical migrations from the Zulu region.
  • D. Umbundu
    Umbundu is a major Bantu language spoken primarily in central and southern Angola, especially by the Ovimbundu people.
  • E. Tshiluba
    Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd27afe7c8190984e10d3f3d5586b completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bbc416c81908774782420b54664 completed March 9, 2026, 8:21 p.m.
Created at: March 6, 2026, 9:47 p.m.