Triple

T21703434
Position Surface form Disambiguated ID Type / Status
Subject Bohuslän E535711 entity
Predicate containsTown P847 FINISHED
Object Skärhamn 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: Skärhamn | Statement: [Bohuslän, containsTown, Skärhamn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skärhamn
Context triple: [Bohuslän, containsTown, Skärhamn]
  • A. Skärhamn chosen
    Skärhamn is a coastal town in western Sweden known for its fishing heritage, picturesque harbor, and the Nordic Watercolour Museum.
  • B. Härnösand
    Härnösand is a coastal city in northern Sweden known for its historic architecture, maritime heritage, and role as an administrative and cultural center in the 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. Fredrikshamn
    Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
  • E. Skärholmen
    Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
  • 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_69e0c46b44c0819088ab883ebd44e0e8 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef9b82901c81909de242c920fbc164 completed April 27, 2026, 5:23 p.m.
Created at: April 16, 2026, 6:46 p.m.