Triple

T12033764
Position Surface form Disambiguated ID Type / Status
Subject Bani River E286479 entity
Predicate languageOfName P15 FINISHED
Object Bambara 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: Bambara | Statement: [Bani River, languageOfName, Bambara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bambara
Context triple: [Bani River, languageOfName, Bambara]
  • 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. Dioula
    Dioula is a Mande language of West Africa, widely used as a trade and lingua franca language in countries like Burkina Faso, Côte d’Ivoire, and Mali.
  • C. Dosso Zarma
    Dosso Zarma is a major regional variety of the Zarma language spoken primarily around the Dosso area of Niger.
  • D. Mandingo
    Mandingo is a controversial 1975 American film set on a Southern slave plantation, known for its graphic depiction of slavery, racism, and sexual exploitation.
  • E. Mòoré
    Mòoré is a major Gur language spoken primarily by the Mossi people in Burkina Faso and surrounding West African countries.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040724ec8190808f334013ddc6d6 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d6ec4b8819093ff50254a851444 completed May 1, 2026, 12:32 p.m.
Created at: April 8, 2026, 9:47 p.m.