Triple

T14604310
Position Surface form Disambiguated ID Type / Status
Subject Venezuelan peso E342786 entity
Predicate denominationSystem P8049 FINISHED
Object peso and real E876589 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: peso and real | Statement: [Venezuelan peso, denominationSystem, peso and real]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: peso and real
Context triple: [Venezuelan peso, denominationSystem, peso and real]
  • A. peso chosen
    The peso is a monetary unit used as the official currency in several Latin American countries and the Philippines, originating from the Spanish colonial silver coin.
  • B. Peso
    Peso is the gentle penguin medic of the Octonauts crew, known for his caring nature and dedication to helping injured sea creatures.
  • C. peso boliviano
    The peso boliviano was Bolivia’s former national currency, used before the introduction of the boliviano.
  • D. Pesa
    Pesa is a Polish manufacturer of rail vehicles, particularly known for producing modern trams and trains used in various European cities.
  • E. Pesa
    The Pesa is a river in Tuscany, central Italy, known for flowing through the Chianti region before joining the Arno.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44bf67c8190b4c48a7715f9443e completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94ce6c208190a732f1a25700f07c completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.