Triple

T18797022
Position Surface form Disambiguated ID Type / Status
Subject Vendsyssel E459660 entity
Predicate hasMajorTown P316 FINISHED
Object Hirtshals 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: Hirtshals | Statement: [Vendsyssel, hasMajorTown, Hirtshals]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hirtshals
Context triple: [Vendsyssel, hasMajorTown, Hirtshals]
  • A. Hirtshals chosen
    Hirtshals is a Danish coastal town in northern Jutland known for its busy fishing and ferry port on the Skagerrak and its role as a key transport hub between Denmark and Norway.
  • B. Frederikshavn
    Frederikshavn is a port town in northern Jutland, Denmark, known for its ferry connections to Norway and Sweden and its maritime industry.
  • C. Faaborg
    Faaborg is a historic coastal town on the island of Funen in southern Denmark, known for its well-preserved old town, harbor, and cultural attractions.
  • D. Korsør
    Korsør is a Danish coastal town on the island of Zealand, known for its strategic position by the Great Belt strait and its historic maritime and military significance.
  • E. Skælskør
    Skælskør is a small coastal town in western Zealand, Denmark, known for its historic harbor, scenic fjord, and traditional Danish architecture.
  • 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a020821881909749f6a1c6cd195b completed April 20, 2026, 3:40 a.m.
Created at: April 10, 2026, 11:53 a.m.