Triple

T21858803
Position Surface form Disambiguated ID Type / Status
Subject Bosnian dinar E539702 entity
Predicate exchangeRateToGermanMark P64907 FINISHED
Object 1 convertible mark = 1 German mark (via peg) LITERAL 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: 1 convertible mark = 1 German mark (via peg) | Statement: [Bosnian dinar, exchangeRateToGermanMark, 1 convertible mark = 1 German mark (via peg)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: exchangeRateToGermanMark
Context triple: [Bosnian dinar, exchangeRateToGermanMark, 1 convertible mark = 1 German mark (via peg)]
  • A. exchangeRateToPapiermark
    Indicates the conversion rate or value of one currency in terms of the Papiermark.
  • B. exchangeRateToReichsmark
    Indicates the conversion rate or value of one currency in terms of Reichsmarks.
  • C. fixedExchangeRateToDEM chosen
    Indicates that the value of one currency is pegged at a fixed exchange rate relative to the German Deutsche Mark (DEM).
  • D. exchangeRateToPoundSterling
    Indicates the rate at which one unit of a given currency can be converted into British pounds sterling.
  • E. exchangeRateToCUPBeforeUnification
    Indicates the conversion rate that applied to an entity’s value when converting into Cuban pesos (CUP) prior to the currency unification.
  • F. None of above.

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_69e0c47829648190bbe2d1d7033768ec completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0d63944d88190b6bd5e6ba4cc8ec1 completed April 28, 2026, 3:46 p.m.
PD Predicate disambiguation batch_69e6be9394f88190945ddd1dc004d29d completed April 21, 2026, 12:02 a.m.
Created at: April 16, 2026, 6:56 p.m.