Triple

T1143621
Position Surface form Disambiguated ID Type / Status
Subject Vaucluse E23512 entity
Predicate borders P224 FINISHED
Object Var E84932 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: Var | Statement: [Vaucluse, borders, Var]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Var
Context triple: [Vaucluse, borders, Var]
  • A. Var chosen
    Var is a department in southeastern France known for its Mediterranean coastline, including popular resort areas along the French Riviera.
  • B. Varig
    Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
  • C. Val
    Val is the Allied reporting name for the Aichi D3A, a Japanese World War II carrier-based dive bomber used prominently in early Pacific naval battles.
  • D. Vy
    Vy is a major Norwegian railway and public transport company operating regional, intercity, and commuter train services across Norway and parts of Sweden.
  • E. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc4e93d48190b9fea886bf61aad7 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59b2395c81909d4608bdaf1d57e8 completed March 7, 2026, 5 p.m.
Created at: March 1, 2026, 7:44 p.m.