Triple

T9638266
Position Surface form Disambiguated ID Type / Status
Subject Umeå E232990 entity
Predicate hasAirport P105 FINISHED
Object Umeå Airport E523677 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: Umeå Airport | Statement: [Umeå, hasAirport, Umeå Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umeå Airport
Context triple: [Umeå, hasAirport, Umeå Airport]
  • A. Umeå Airport chosen
    Umeå Airport is a regional airport in northern Sweden serving the city of Umeå with domestic and limited international flights.
  • B. Luleå Airport
    Luleå Airport is a major civilian and military airport in northern Sweden serving the city of Luleå and the wider Norrbotten region.
  • C. Uppsala Airport
    Uppsala Airport is a Swedish airfield near the city of Uppsala, primarily used for military and general aviation rather than large-scale commercial passenger traffic.
  • D. Ronneby Airport
    Ronneby Airport is a regional airport in southern Sweden serving the Ronneby and Blekinge area with domestic flights and operated as part of the national airport network.
  • E. Kiruna Airport
    Kiruna Airport is a regional airport in northern Sweden serving the town of Kiruna and the surrounding Arctic region, including access to the nearby space research and tourism activities.
  • 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_69ca848a5a908190aad251f4137b0c3a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b51b08081908e30744607b28953 completed April 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18243cfdc81908ecdf039c38de478 completed April 4, 2026, 9:27 p.m.
Created at: March 30, 2026, 8:11 p.m.