Triple

T3909280
Position Surface form Disambiguated ID Type / Status
Subject Kigali E87281 entity
Predicate currency P245 FINISHED
Object Rwandan franc E134534 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: Rwandan franc | Statement: [Kigali, currency, Rwandan franc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rwandan franc
Context triple: [Kigali, currency, 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. West African CFA franc
    The West African CFA franc is a regional currency used by several West African countries, issued by the Central Bank of West African States and pegged to the euro.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed14d6d08190b74757eb9288fe4d completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51cb1b194819093b88d3f37ae51d9 completed March 14, 2026, 8:30 a.m.
Created at: March 9, 2026, 3:22 p.m.