Triple

T12653678
Position Surface form Disambiguated ID Type / Status
Subject Jula E302226 entity
Predicate closelyRelatedTo P37 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: [Jula, closelyRelatedTo, Bambara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bambara
Context triple: [Jula, closelyRelatedTo, 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96160730c81909e1aa3efb51bf159 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684dd133481909ce06b8b1fd5a5e3 completed May 2, 2026, 11:12 p.m.
Created at: April 9, 2026, 5:18 p.m.