Triple

T797168
Position Surface form Disambiguated ID Type / Status
Subject Latvia E17048 entity
Predicate memberOf P10 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: [Latvia, memberOf, Eurozone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurozone
Context triple: [Latvia, memberOf, 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. European Union
    The European Union is a political and economic union of European countries that collectively form one of the world’s largest single markets and play a major role in global diplomacy and governance.
  • D. Schengen Area
    The Schengen Area is a zone of European countries that have abolished internal border controls to allow passport-free movement of people across most of the continent.
  • E. 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.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7b342888190a344fe81a2c9f33c completed March 1, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b83f0fb4819097f29c9ab90cf1a8 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:38 p.m.