Triple

T14361329
Position Surface form Disambiguated ID Type / Status
Subject Kuntaur E356106 entity
Predicate hasLanguage P15 FINISHED
Object Fula E9155 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: Fula | Statement: [Kuntaur, hasLanguage, Fula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fula
Context triple: [Kuntaur, hasLanguage, Fula]
  • A. Fulani chosen
    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.
  • B. 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.
  • C. Guinean Fula
    Guinean Fula is a regional variety of the Fula (Fulani) language spoken primarily in Guinea.
  • D. 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.
  • E. 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.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f54bfb08190a27c0d12731acec2 completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4aba788190bd5ab8cbc772dcf1 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:15 a.m.