Triple

T14399846
Position Surface form Disambiguated ID Type / Status
Subject National Museum of Niger E357040 entity
Predicate languageOfWorkOrName P15 FINISHED
Object Zarma E160218 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: Zarma | Statement: [National Museum of Niger, languageOfWorkOrName, Zarma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zarma
Context triple: [National Museum of Niger, languageOfWorkOrName, Zarma]
  • A. Zarma language chosen
    The Zarma language is a widely spoken Nilo-Saharan language of West Africa, primarily used in Niger and neighboring countries, and serves as a major lingua franca in the region.
  • B. Guinean Fula
    Guinean Fula is a regional variety of the Fula (Fulani) language spoken primarily in Guinea.
  • C. 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.
  • D. Casamance Mandinka
    Casamance Mandinka is a regional variety of the Mandinka language spoken primarily in the Casamance area of southern Senegal.
  • E. Bambara
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9083f9d081908fe5c99655c410b3 completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bc424f88190ab3a1c1aec61cb40 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:17 a.m.