Triple

T12802577
Position Surface form Disambiguated ID Type / Status
Subject German mark E306058 entity
Predicate replacedBy P101 FINISHED
Object euro E416311 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: [German mark, replacedBy, euro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: euro
Context triple: [German mark, replacedBy, euro]
  • A. euro chosen
    The euro is the official common currency used by most countries in the European Union and one of the world's major reserve and trading currencies.
  • B. EUR
    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.
  • C. EURO
    EURO is the commonly used short name for the UEFA European Championship, the premier international football tournament for national teams in Europe.
  • D. 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.
  • E. DSACEUR
    DSACEUR is the acronym for the Deputy Supreme Allied Commander Europe, a senior NATO military leadership position.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e7e3be48190ba9159c9f1ac2ccd completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ec0d5dc819099a8036c6cbac634 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:30 p.m.