Triple

T10247690
Position Surface form Disambiguated ID Type / Status
Subject CFA franc E240259 entity
Predicate usedBy P260 FINISHED
Object Burkina Faso E42862 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: Burkina Faso | Statement: [CFA franc, usedBy, Burkina Faso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burkina Faso
Context triple: [CFA franc, usedBy, Burkina Faso]
  • A. Burkina Faso chosen
    Burkina Faso is a landlocked West African country known for its diverse cultures, Sahelian landscapes, and capital city, Ouagadougou.
  • B. Mali
    Mali is a landlocked West African country known for its historic trading cities like Timbuktu, rich Sahelian culture, and significant role in the ancient Mali Empire.
  • C. Benin
    Benin is a West African country on the Gulf of Guinea known for its historical Kingdom of Dahomey and as a key region in the transatlantic slave trade.
  • D. Republic of Guinea
    The Republic of Guinea is a West African country rich in natural resources, particularly bauxite, with a predominantly Muslim population and a history of French colonial rule.
  • E. Tenkodogo, Burkina Faso
    Tenkodogo is a historic town in eastern Burkina Faso, considered one of the country’s oldest settlements and an important regional center for the Gurma people.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d22e0d4c8190a6712859924e9d3d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7936ce4819087f07df2c7a76282 completed April 9, 2026, 12:49 a.m.
Created at: April 6, 2026, 11:27 a.m.