Triple

T5261509
Position Surface form Disambiguated ID Type / Status
Subject Varig E118834 entity
Predicate abbreviation P43 FINISHED
Object VARIG E118834 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: VARIG | Statement: [Varig, abbreviation, VARIG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VARIG
Context triple: [Varig, abbreviation, 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. Var
    Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
  • C. Var
    Var is a Norse goddess associated with oaths, agreements, and the punishment of those who break them.
  • D. VAR
    VAR (Video Assistant Referee) is a football officiating system that uses video technology to help referees review and correct clear and obvious errors in key match situations.
  • E. Vara
    Vara is a short form of the female given name Varvara, commonly used in Slavic languages.
  • 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_69bd446a42c88190b7ecbef006561d55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bd0c5f48190a1be89314c59f96b completed March 20, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe85a3f88190ae014b18b1df202e completed March 21, 2026, 8:24 p.m.
Created at: March 20, 2026, 1:50 p.m.