Triple

T20614868
Position Surface form Disambiguated ID Type / Status
Subject Viação Aérea Rio-Grandense E506538 entity
Predicate hasAbbreviation P43 FINISHED
Object VARIG NE NERFINISHED

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: VARIG | Statement: [Viação Aérea Rio-Grandense, hasAbbreviation, VARIG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VARIG
Context triple: [Viação Aérea Rio-Grandense, hasAbbreviation, VARIG]
  • A. Varig chosen
    Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
  • B. Varia
    Varia is a village on the island of Lesbos in Greece, known for hosting the Tériade Museum of Modern Art.
  • C. Varvarco
    Varvarco is a small town in Argentina’s Neuquén Province, known as a gateway to the Domuyo volcanic region and its surrounding Andean landscapes.
  • D. Var
    Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
  • E. Var
    Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aadaf47881909e93efb535c6c1e3 completed April 20, 2026, 10:38 p.m.
Created at: April 16, 2026, 11:41 a.m.