Triple

T21052954
Position Surface form Disambiguated ID Type / Status
Subject Visby Airport E518634 entity
Predicate servesRegion P82 FINISHED
Object Gotland 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: Gotland | Statement: [Visby Airport, servesRegion, Gotland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gotland
Context triple: [Visby Airport, servesRegion, Gotland]
  • A. Gotland chosen
    Gotland is Sweden’s largest island, located in the Baltic Sea and known for its medieval town of Visby, limestone cliffs, and rich Viking-era history.
  • B. Gødland
    Gødland is a psychedelic, retro-styled science fiction comic book series that pays homage to classic cosmic superhero tales, created by writer Joe Casey and artist Tom Scioli.
  • C. Sylt
    Sylt is a popular German North Sea island known for its long sandy beaches, distinctive dune landscapes, and status as an upscale holiday destination.
  • D. Ölandet
    Ölandet is one of the islands in the Pellinge archipelago off the southern coast of Finland, known for its coastal nature and traditional island scenery.
  • E. Öland
    Öland is Sweden’s second-largest island, known for its unique limestone plains, rich birdlife, and popular summer tourism along the Baltic Sea coast.
  • 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_69e0b5053ac48190921529544959e906 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fd7cabe881909e6b258a14d501a6 completed April 21, 2026, 4:30 a.m.
Created at: April 16, 2026, 2:36 p.m.