Triple

T13972507
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg and France E336099 entity
Predicate areMembersOf P27891 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: [Luxembourg and France, areMembersOf, Eurozone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurozone
Context triple: [Luxembourg and France, areMembersOf, 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e8eae40819080dd4bd25c73b6d6 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac90250881908f1945793d261752 completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:18 p.m.