Triple

T22584549
Position Surface form Disambiguated ID Type / Status
Subject R₣ E564752 entity
Predicate representsMonetaryUnit P36099 FINISHED
Object Rwandan franc NE NERFINISHED

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: Rwandan franc | Statement: [R₣, representsMonetaryUnit, Rwandan franc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rwandan franc
Context triple: [R₣, representsMonetaryUnit, Rwandan franc]
  • A. Rwandan franc chosen
    The Rwandan franc is the official monetary unit of Rwanda, used for everyday transactions and issued by the National Bank of Rwanda.
  • B. Burundian franc
    The Burundian franc is the official monetary unit of Burundi, used for all financial transactions and issued by the country's central bank.
  • 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. 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.
  • E. Belgian Congo franc
    The Belgian Congo franc was the colonial currency used in the Belgian Congo and its administered territories, including Ruanda-Urundi, during much of the 20th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615b4fa08190a8d2d66e01db429f completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:44 p.m.