Triple

T15216469
Position Surface form Disambiguated ID Type / Status
Subject Bybanen E363648 entity
Predicate terminus P388 FINISHED
Object Flesland E160361 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: Flesland | Statement: [Bybanen, terminus, Flesland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flesland
Context triple: [Bybanen, terminus, Flesland]
  • A. Gardermoen (Vestby)
    Gardermoen (Vestby) is a small village in Vestby Municipality in Viken county, Norway.
  • B. Bergen Airport, Flesland chosen
    Bergen Airport, Flesland is the main international airport serving the city of Bergen and western Norway, handling both domestic and international flights.
  • C. Sandefjord Airport Torp
    Sandefjord Airport Torp is a regional international airport in southeastern Norway serving Sandefjord and the greater Vestfold area with domestic and European flights.
  • D. Oslo East
    Oslo East is the eastern part of Norway’s capital city, often associated with working-class neighborhoods, cultural diversity, and a strong local football supporter culture.
  • E. Farsund
    Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed343f51481908f04c35d37b39ad2 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.