Triple

T12974541
Position Surface form Disambiguated ID Type / Status
Subject Lillehammer bus terminal E321487 entity
Predicate serves P98 FINISHED
Object Innlandet region E65742 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: Innlandet region | Statement: [Lillehammer bus terminal, serves, Innlandet region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innlandet region
Context triple: [Lillehammer bus terminal, serves, Innlandet region]
  • A. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • B. Innlandet
    Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
  • C. Innlandet chosen
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • D. Jæren region
    The Jæren region is a coastal area in southwestern Norway known for its flat, fertile farmland, long sandy beaches, and the city of Stavanger as its main urban center.
  • E. Dovre region
    The Dovre region is a mountainous area in central Norway known for its rugged landscapes, national parks, and rich wildlife, including wild reindeer.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e4322c08190abd43daadf16097f completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5f4bedc81909b8dfa79a842e12d completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 8:37 p.m.