Triple

T29393502
Position Surface form Disambiguated ID Type / Status
Subject Franc E745432 entity
Predicate usedBeforeEuroIn P54151 FINISHED
Object Eurozone countries using the franc LITERAL 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: Eurozone countries using the franc | Statement: [Franc, usedBeforeEuroIn, Eurozone countries using the franc]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedBeforeEuroIn
Context triple: [Franc, usedBeforeEuroIn, Eurozone countries using the franc]
  • A. adoptedEuro
    Indicates that a country or entity has officially adopted the euro as its legal currency.
  • B. peggedToEuroSince
    Indicates that the value of one currency or financial instrument has been fixed or tightly linked to the euro starting from a specific point in time.
  • C. notAllEUMembersUseEuro
    Indicates that the set of all EU member states is not identical to the set of countries using the euro, i.e., at least one EU member does not use the euro as its official currency.
  • D. usedAsCurrency chosen
    Indicates that something functions as money or a medium of exchange within an economic system.
  • E. usesCurrencyInitially
    Indicates that an entity originally adopts or operates with a particular currency at the start of a defined period or process.
  • F. None of above.

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_69f0a79dfabc81908755382ee47791e2 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f73223675481908c1bc3208c0f5284 completed May 3, 2026, 11:31 a.m.
PD Predicate disambiguation batch_69f7317690108190b3aae2cd2e1d069e completed May 3, 2026, 11:28 a.m.
Created at: April 28, 2026, 2:44 p.m.