Triple

T7965923
Position Surface form Disambiguated ID Type / Status
Subject Borna E185203 entity
Predicate usesCurrency P188 FINISHED
Object Euro E12559 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: Euro | Statement: [Borna, usesCurrency, Euro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Euro
Context triple: [Borna, usesCurrency, Euro]
  • A. Euro chosen
    The Euro is the official common currency used by many countries in the European Union, facilitating trade and travel across much of Europe.
  • B. Eurozone
    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.
  • 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. Euroa
    Euroa is a small rural town in northeastern Victoria, Australia, known for its agricultural surroundings and historic connection to the Kelly Gang bushrangers.
  • 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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ba262208190887169fe94e47b0e completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe09c23388190baf86dcd7df60248 completed March 31, 2026, 2:56 p.m.
Created at: March 30, 2026, 5:12 p.m.