Triple

T9960789
Position Surface form Disambiguated ID Type / Status
Subject Burundian franc E195560 entity
Predicate nameInFrench P6538 FINISHED
Object franc burundais E195560 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: franc burundais | Statement: [Burundian franc, nameInFrench, franc burundais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: franc burundais
Context triple: [Burundian franc, nameInFrench, franc burundais]
  • A. Burundian franc chosen
    The Burundian franc is the official monetary unit of Burundi, used for all financial transactions and issued by the country's central bank.
  • B. Rwandan franc
    The Rwandan franc is the official monetary unit of Rwanda, used for everyday transactions and issued by the National Bank of Rwanda.
  • C. Congolese franc
    The Congolese franc is the official monetary unit used in the Democratic Republic of the Congo for all financial and commercial transactions.
  • D. Djiboutian franc
    The Djiboutian franc is the official monetary unit of Djibouti, a small East African nation strategically located on the Horn of Africa.
  • E. Central African CFA franc
    The Central African CFA franc is a regional currency used by several Central African countries, including Gabon, and is guaranteed by the French Treasury.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6d219c48190b2084b0eb07ae125 completed April 2, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257aa73d4819081f77f8386449905 completed April 5, 2026, 12:38 p.m.
Created at: March 30, 2026, 8:47 p.m.