Triple

T11736752
Position Surface form Disambiguated ID Type / Status
Subject Ringsted E279045 entity
Predicate hasNearbyCity P350 FINISHED
Object Næstved E272601 NE FINISHED

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: Næstved | Statement: [Ringsted, hasNearbyCity, Næstved]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Næstved
Context triple: [Ringsted, hasNearbyCity, Næstved]
  • A. Næstved chosen
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • B. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • C. Holbæk
    Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural center.
  • D. Birkerød
    Birkerød is a suburban town in northeastern Zealand, Denmark, known for its residential character, green surroundings, and proximity to Copenhagen.
  • E. Gladsaxe
    Gladsaxe is a municipality in the northern suburbs of Copenhagen, Denmark, known for its residential areas, green spaces, and role as part of the Greater Copenhagen urban region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1308339ac8190b579a8c1bee2a2c2 completed April 28, 2026, 10:11 p.m.
Created at: April 8, 2026, 9:41 p.m.