Triple

T21330737
Position Surface form Disambiguated ID Type / Status
Subject European route E22 E525890 entity
Predicate passesThroughCity P416 FINISHED
Object Karlshamn NE NERFINISHED

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: Karlshamn | Statement: [European route E22, passesThroughCity, Karlshamn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karlshamn
Context triple: [European route E22, passesThroughCity, Karlshamn]
  • A. Karlshamn chosen
    Karlshamn is a coastal town in southern Sweden known for its harbor, archipelago, and role as a regional industrial and transport hub.
  • B. Oskarshamn
    Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
  • C. Eskilstuna
    Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
  • 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. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51b90788190a4dd823d962626da completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7ab5177dc8190b888351e9a45b45f completed April 21, 2026, 4:52 p.m.
Created at: April 16, 2026, 4:42 p.m.