Triple

T23358749
Position Surface form Disambiguated ID Type / Status
Subject Nynäshamn–Ventspils route E593124 entity
Predicate originCity P1041 FINISHED
Object Nynäshamn 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: Nynäshamn | Statement: [Nynäshamn–Ventspils route, originCity, Nynäshamn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nynäshamn
Context triple: [Nynäshamn–Ventspils route, originCity, Nynäshamn]
  • A. Nynäshamn chosen
    Nynäshamn is a coastal town in Stockholm County, Sweden, known for its ferry connections to Gotland and the Baltic states as well as its scenic archipelago setting.
  • 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. Fredrikshamn
    Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
  • D. Skärhamn
    Skärhamn is a coastal town in western Sweden known for its fishing heritage, picturesque harbor, and the Nordic Watercolour Museum.
  • E. Kristinehamn
    Kristinehamn is a small Swedish town in Värmland County known for its lakeside location on Vänern and its historical role as a regional trading and industrial center.
  • 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_69e25d24d2a4819092e6ede74c2a918d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19a196b308190bfe9bb4b6e7ec363 completed April 29, 2026, 5:41 a.m.
Created at: April 17, 2026, 5:29 p.m.