Triple

T4376855
Position Surface form Disambiguated ID Type / Status
Subject Gothenburg Landvetter Airport E99027 entity
Predicate operator P179 FINISHED
Object Swedavia E111378 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: Swedavia | Statement: [Gothenburg Landvetter Airport, operator, Swedavia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swedavia
Context triple: [Gothenburg Landvetter Airport, operator, Swedavia]
  • A. Swedavia chosen
    Swedavia is a Swedish state-owned company that owns, operates, and develops several of Sweden’s major airports.
  • B. Sweden
    Sweden is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and long-standing policy of neutrality.
  • C. Gustafs, Sweden
    Gustafs is a small locality in Dalarna County, central Sweden, known as a rural community within the municipality of Säter.
  • D. Nordavia
    Nordavia was a Russian regional airline that rebranded as Smartavia, operating domestic and some international routes primarily from northern Russia.
  • E. Svealand
    Svealand is the central region of Sweden, historically significant as the country's core area and home to the capital city, Stockholm.
  • 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_69b3454ea8f48190a49c2436624d6ef6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3523ed220819090cef1a7933489d9 completed March 12, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e51907688190ad964d341eb84529 completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:18 p.m.