Triple

T1705283
Position Surface form Disambiguated ID Type / Status
Subject NLG E36858 entity
Predicate replacedBy P101 FINISHED
Object EUR E24672 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: EUR | Statement: [NLG, replacedBy, EUR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EUR
Context triple: [NLG, replacedBy, EUR]
  • A. EUR chosen
    EUR is the commonly used abbreviation for the Bureau of European and Eurasian Affairs within the U.S. Department of State, which oversees American foreign policy and diplomatic relations in Europe and Eurasia.
  • B. EURO
    EURO is the commonly used short name for the UEFA European Championship, the premier international football tournament for national teams in 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
    The Euro is the official common currency used by many countries in the European Union, facilitating trade and travel across much of Europe.
  • E. Swiss franc
    The Swiss franc is the official currency of Switzerland and Liechtenstein, known for its stability and status as a major global reserve currency.
  • 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_69a88617439c819094ffb5d16a0f6307 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62f3a5a08190a2b90d9492c3192e completed March 6, 2026, 5:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ad3b9c481909f83f7045789e49d completed March 8, 2026, 2:42 p.m.
Created at: March 4, 2026, 7:30 p.m.