Triple

T5248973
Position Surface form Disambiguated ID Type / Status
Subject European route E4 E118533 entity
Predicate passesThrough P225 FINISHED
Object Skellefteå E351191 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: Skellefteå | Statement: [European route E4, passesThrough, Skellefteå]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skellefteå
Context triple: [European route E4, passesThrough, Skellefteå]
  • A. Skellefteå chosen
    Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
  • B. Luleå
    Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
  • C. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • 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. Östersund
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • 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_69c11c83f8bc8190bdf139c9da2dd66b completed March 23, 2026, 10:57 a.m.
Created at: March 20, 2026, 1:50 p.m.