Triple

T7394565
Position Surface form Disambiguated ID Type / Status
Subject Oslo Metro Line 1 E170589 entity
Predicate terminus P388 FINISHED
Object Frognerseteren E163011 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: Frognerseteren | Statement: [Oslo Metro Line 1, terminus, Frognerseteren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frognerseteren
Context triple: [Oslo Metro Line 1, terminus, Frognerseteren]
  • A. Frognerseteren chosen
    Frognerseteren is a hilltop area in Oslo, Norway, known for its panoramic views over the city, traditional wooden restaurant, and access to popular hiking and skiing trails.
  • B. Skøyen
    Skøyen is a neighborhood in western Oslo, Norway, known as a busy residential and commercial hub with strong public transport connections.
  • C. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • D. Kolsås
    Kolsås is a suburban area in Bærum, Norway, known as the endpoint of one of the Oslo Metro lines and for its nearby forested hill popular for hiking and climbing.
  • E. Lyngseidet
    Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
  • 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2263b48819089319a2a2f0d3357 completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c810fcb1408190a6ed22213bd7830b completed March 28, 2026, 5:33 p.m.
Created at: March 27, 2026, 3:09 p.m.