Triple

T6999972
Position Surface form Disambiguated ID Type / Status
Subject forint E162310 entity
Predicate notPartOf P1611 FINISHED
Object eurozone E2721 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: eurozone | Statement: [forint, notPartOf, eurozone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: eurozone
Context triple: [forint, notPartOf, eurozone]
  • A. Eurozone chosen
    The Eurozone is the group of European Union countries that have adopted the euro as their common official currency and share a unified monetary policy.
  • B. Euro
    The Euro is the official common currency used by many countries in the European Union, facilitating trade and travel across much of Europe.
  • C. EURO
    EURO is the commonly used abbreviation for the World Health Organization’s Regional Office for Europe, which oversees public health initiatives across the European region.
  • D. EURO
    EURO is the commonly used short name for the UEFA European Championship, the premier international football tournament for national teams in Europe.
  • E. euro
    The euro is the official common currency used by most countries in the European Union and one of the world's major reserve and trading currencies.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc0e54c88190b092870f2d128510 completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a2c510c8190b7c86f8b399388ae completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:33 p.m.