Triple

T5652461
Position Surface form Disambiguated ID Type / Status
Subject Norwegian railway network E124536 entity
Predicate connectsCity P4245 FINISHED
Object Stavanger E74350 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: Stavanger | Statement: [Norwegian railway network, connectsCity, Stavanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stavanger
Context triple: [Norwegian railway network, connectsCity, Stavanger]
  • A. Stavanger chosen
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • B. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • C. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • D. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • E. Bergen
    Bergen is a city in western Germany, historically notable as the site of the 1759 Battle of Bergen during the Seven Years' War.
  • 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_69c00825df388190a58742fa9b1aa33d completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022d8a2588190b10de59edbc8841f completed March 22, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141158f188190af1a981614e8528e completed March 23, 2026, 1:33 p.m.
Created at: March 22, 2026, 3:42 p.m.