Triple

T12754613
Position Surface form Disambiguated ID Type / Status
Subject Belgium and France E304824 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: [Belgium and France, memberOf, Eurozone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurozone
Context triple: [Belgium and France, 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. European Economic Area
    The European Economic Area is a regional agreement that extends the European Union’s single market to certain non-EU countries, allowing them to participate in the free movement of goods, services, people, and capital.
  • E. EU
    EU is the vehicle registration code for the German district of Euskirchen in the state of North Rhine-Westphalia.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d89ea70819098c470344f172167 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c9aa6308190bfcb1511a561c0f9 completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:27 p.m.