Triple

T10882452
Position Surface form Disambiguated ID Type / Status
Subject 5N E256955 entity
Predicate airlineName P9049 FINISHED
Object Smartavia E44282 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: Smartavia | Statement: [5N, airlineName, Smartavia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Smartavia
Context triple: [5N, airlineName, Smartavia]
  • A. Smartavia chosen
    Smartavia is a Russian low-cost airline that operates domestic and regional flights, using Moscow Domodedovo International Airport as one of its main bases.
  • B. Edelweiss Air
    Edelweiss Air is a Swiss leisure airline based in Zurich that operates holiday and charter flights to vacation destinations worldwide.
  • C. Crossair
    Crossair was a former Swiss regional airline that served as the main predecessor to Swiss International Air Lines after the collapse of Swissair.
  • D. Ibex Airlines
    Ibex Airlines is a Japanese regional airline that operates domestic routes, often connecting smaller cities and regional airports within Japan.
  • E. Okay Airways
    Okay Airways is a Chinese airline headquartered in Beijing that operates domestic and regional flights, known as China's first private-sector airline.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751db24208190b3a7ed7eea118522 completed April 9, 2026, 7:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69e154e49ab08190b522b5361ac65c01 completed April 16, 2026, 9:30 p.m.
Created at: April 8, 2026, 9:21 p.m.