Triple

T21175390
Position Surface form Disambiguated ID Type / Status
Subject Port of Nynäshamn E521797 entity
Predicate hasRouteTo P4374 FINISHED
Object Visby 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: Visby | Statement: [Port of Nynäshamn, hasRouteTo, Visby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Visby
Context triple: [Port of Nynäshamn, hasRouteTo, Visby]
  • A. Visby chosen
    Visby is a well-preserved medieval Hanseatic town on the Swedish island of Gotland, renowned for its historic city wall and UNESCO World Heritage status.
  • B. Karlskrona
    Karlskrona is a historic Swedish coastal city and naval base known for its well-preserved maritime architecture and UNESCO-listed naval port.
  • C. Halmstad
    Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
  • D. Halmstad
    Halmstad is a village in Moss municipality in Viken county, southeastern Norway.
  • E. Kristianstad
    Kristianstad is a historic city in southern Sweden known for its well-preserved Renaissance architecture and proximity to the wetlands of the Kristianstad Vattenrike Biosphere Reserve.
  • 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_69e0b50e30748190b186824a206d39b9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7271597288190b04baff9ca8d866c completed April 21, 2026, 7:28 a.m.
Created at: April 16, 2026, 3 p.m.