Triple

T1340527
Position Surface form Disambiguated ID Type / Status
Subject Bambara E28452 entity
Predicate alsoKnownAs P39 FINISHED
Object Bamana E28452 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: Bamana | Statement: [Bambara, alsoKnownAs, Bamana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamana
Context triple: [Bambara, alsoKnownAs, Bamana]
  • A. Bambara chosen
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
  • B. Mandinka
    Mandinka is a major Mande language spoken primarily in The Gambia, Senegal, Guinea-Bissau, and neighboring West African countries by the Mandinka people.
  • 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. Baoulé language
    The Baoulé language is a Niger-Congo language spoken primarily by the Baoulé people of central Côte d'Ivoire.
  • E. Fulani
    The Fulani are a large, traditionally pastoralist West African ethnic group spread across many countries, known for their nomadic cattle-herding culture, Islamic scholarship, and significant historical role in regional empires and trade.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c21490488190b4281a16c87677d1 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace56298708190819518926b2b608f completed March 8, 2026, 2:56 a.m.
Created at: March 1, 2026, 7:56 p.m.