Triple

T13400566
Position Surface form Disambiguated ID Type / Status
Subject Turning Torso E319815 entity
Predicate precededBy P97 FINISHED
Object Kaknästornet
Kaknästornet is a prominent telecommunications and observation tower in Stockholm, Sweden, known for its modernist design and panoramic city views.
E1039076 NE FINISHED

How this triple was built (4 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: [Turning Torso, precededBy, Kaknästornet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaknästornet
Context triple: [Turning Torso, precededBy, Kaknästornet]
  • A. Gustavsberg
    Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
  • B. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • C. Åreskutan
    Åreskutan is a prominent mountain in central Sweden known for hosting one of Scandinavia’s most popular ski resorts and extensive alpine facilities.
  • D. Skanstull
    Skanstull is a district in southern central Stockholm, Sweden, known as a major traffic junction and gateway to the island of Södermalm.
  • E. Kallhäll
    Kallhäll is a suburban district in the Stockholm metropolitan area of Sweden, known for its residential neighborhoods and commuter connections.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kaknästornet
Triple: [Turning Torso, precededBy, Kaknästornet]
Generated description
Kaknästornet is a prominent telecommunications and observation tower in Stockholm, Sweden, known for its modernist design and panoramic city views.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kaknästornet
Target entity description: Kaknästornet is a prominent telecommunications and observation tower in Stockholm, Sweden, known for its modernist design and panoramic city views.
  • A. Gustavsberg
    Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
  • B. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • C. Åreskutan
    Åreskutan is a prominent mountain in central Sweden known for hosting one of Scandinavia’s most popular ski resorts and extensive alpine facilities.
  • D. Skanstull
    Skanstull is a district in southern central Stockholm, Sweden, known as a major traffic junction and gateway to the island of Södermalm.
  • E. Kallhäll
    Kallhäll is a suburban district in the Stockholm metropolitan area of Sweden, known for its residential neighborhoods and commuter connections.
  • F. None of above. chosen

Provenance (5 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbae47e99081909d8b5dba97a11988 completed April 12, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73076a7ac8190bd7898edff7d90e8 completed May 3, 2026, 11:24 a.m.
NEDg Description generation batch_69f732351cf88190be85186d20b529b7 completed May 3, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_69f732d82c308190907e11de42e2c8ea completed May 3, 2026, 11:34 a.m.
Created at: April 9, 2026, 9:34 p.m.