Triple

T20707872
Position Surface form Disambiguated ID Type / Status
Subject Asker Line E508951 entity
Predicate servesStation P839 FINISHED
Object Lysaker Station 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: Lysaker Station | Statement: [Asker Line, servesStation, Lysaker Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lysaker Station
Context triple: [Asker Line, servesStation, Lysaker Station]
  • A. Lysaker Station chosen
    Lysaker Station is a major railway station in the Oslo metropolitan area of Norway, serving as an important commuter and regional transport hub.
  • B. Skøyen Station
    Skøyen Station is a major railway and commuter hub in Oslo, Norway, serving regional and local trains as part of the city's western transport corridor.
  • C. Drammen Station
    Drammen Station is a major railway hub in Drammen, Norway, connecting regional and long-distance train services to Oslo and other parts of the country.
  • D. Røa station
    Røa station is a suburban rapid transit stop on the Oslo Metro serving the Røa neighborhood in western Oslo, Norway.
  • E. Bjorli Station
    Bjorli Station is a railway station in the village of Bjorli in Lesja, Norway, serving as a stop on the Rauma Line through the Romsdalen valley.
  • 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_69e0b4c40ad88190b81f77695366d328 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1952e888190877b79933970f7b0 completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:14 p.m.