Triple

T5248971
Position Surface form Disambiguated ID Type / Status
Subject European route E4 E118533 entity
Predicate passesThrough P225 FINISHED
Object Örnsköldsvik E335730 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: Örnsköldsvik | Statement: [European route E4, passesThrough, Örnsköldsvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Örnsköldsvik
Context triple: [European route E4, passesThrough, Örnsköldsvik]
  • A. Örnsköldsvik chosen
    Örnsköldsvik is a coastal town in northern Sweden known for its strong ice hockey tradition and as the hometown of several prominent NHL players.
  • B. Östersund
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • C. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • D. Karlskoga
    Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
  • E. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b787b34819081af96de9355bb4f completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107a4786881908a5fdd26e65e949b completed March 23, 2026, 9:28 a.m.
Created at: March 20, 2026, 1:50 p.m.