Triple

T21374258
Position Surface form Disambiguated ID Type / Status
Subject Lysaker E527154 entity
Predicate hasBusTerminal P5891 FINISHED
Object Lysaker bus terminal 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 bus terminal | Statement: [Lysaker, hasBusTerminal, Lysaker bus terminal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lysaker bus terminal
Context triple: [Lysaker, hasBusTerminal, Lysaker bus terminal]
  • A. Lysaker bus terminal chosen
    Lysaker bus terminal is a public transport hub in Lysaker, Norway, serving as a key interchange point for regional and local bus services.
  • B. Oslo Bus Terminal
    Oslo Bus Terminal is the main long-distance and regional bus hub in Oslo, Norway, connecting the city with domestic and international destinations.
  • C. Lillehammer bus terminal
    Lillehammer bus terminal is the main hub for local and regional bus services in Lillehammer, Norway, providing connections within the town and to surrounding areas.
  • D. Lysaker Station
    Lysaker Station is a major railway station in the Oslo metropolitan area of Norway, serving as an important commuter and regional transport hub.
  • E. 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.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0b3666c8190a83bb32eeba24105 completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:10 p.m.