Triple

T23478270
Position Surface form Disambiguated ID Type / Status
Subject Freden i Fredrikshamn E570329 entity
Predicate signedIn P441 FINISHED
Object Fredrikshamn 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: Fredrikshamn | Statement: [Freden i Fredrikshamn, signedIn, Fredrikshamn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fredrikshamn
Context triple: [Freden i Fredrikshamn, signedIn, Fredrikshamn]
  • A. Fredrikshamn chosen
    Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
  • B. Söderhamn
    Söderhamn is a coastal town in east-central Sweden known for its historical wooden architecture and role as the administrative and commercial center of the surrounding region.
  • C. Hammarö
    Hammarö is a Swedish island and municipality in Värmland County, known for its forests, coastline, and proximity to the city of Karlstad.
  • D. Hässleholm
    Hässleholm is a town in southern Sweden’s Skåne County known as a regional railway hub and service center.
  • E. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • 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_69e245af8a88819084f2704f6d265a92 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a74e7e648190b89006dce7d7ce05 completed April 29, 2026, 6:38 a.m.
Created at: April 17, 2026, 6:02 p.m.