Triple

T5290763
Position Surface form Disambiguated ID Type / Status
Subject SJ Norge E119734 entity
Predicate serviceArea P82 FINISHED
Object Nordland E80792 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: Nordland | Statement: [SJ Norge, serviceArea, Nordland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordland
Context triple: [SJ Norge, serviceArea, Nordland]
  • A. Nordland chosen
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • B. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • C. Finnmark
    Finnmark is a sparsely populated, historically Norwegian region in the far northeast of Scandinavia, known for its Arctic climate, Sami culture, and dramatic coastal and tundra landscapes.
  • D. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • E. Troms og Finnmark
    Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eac7b88190900142bd1310c0fd completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06f066988190a3df7e270df84fdd completed March 21, 2026, 9 p.m.
Created at: March 20, 2026, 1:52 p.m.