Triple

T17391352
Position Surface form Disambiguated ID Type / Status
Subject Royal National City Park E422829 entity
Predicate contains P35 FINISHED
Object Kaknästornet 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: Kaknästornet | Statement: [Royal National City Park, contains, Kaknästornet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaknästornet
Context triple: [Royal National City Park, contains, Kaknästornet]
  • A. Kaknästornet chosen
    Kaknästornet is a prominent telecommunications and observation tower in Stockholm, Sweden, known for its modernist design and panoramic city views.
  • B. Skarpnäck
    Skarpnäck is a residential district in southern Stockholm, Sweden, known for its postwar housing areas and as the terminus of the green line on the Stockholm metro.
  • C. Gustavsberg
    Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
  • D. Vårberg
    Vårberg is a residential district in southern Stockholm, Sweden, known for its suburban housing areas and proximity to Lake Mälaren.
  • E. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • 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_69d889d710288190bf0f4762801fefae completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43aba5398819096846bdeefde0788 completed April 19, 2026, 2:15 a.m.
Created at: April 10, 2026, 5:45 a.m.