Triple

T22611650
Position Surface form Disambiguated ID Type / Status
Subject Lørenskog municipality E566718 entity
Predicate hasIndoorSkiArena P148932 FINISHED
Object SNØ NE NERFINISHED

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: SNØ | Statement: [Lørenskog municipality, hasIndoorSkiArena, SNØ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SNØ
Context triple: [Lørenskog municipality, hasIndoorSkiArena, SNØ]
  • A. Snoge
    Snoge is the historic 17th-century Portuguese-Israelite synagogue in Amsterdam, renowned as one of the oldest and best-preserved Sephardic synagogues in Europe.
  • B. Sno
    Sno is a small mountain village in northeastern Georgia’s Kazbegi region, known for its traditional stone towers and scenic Caucasus landscapes.
  • C. Snowdown
    Snowdown is a former coal mining village in the Kent coalfield of southeast England, historically centered around Snowdown Colliery and its mining community.
  • D. SK Snøgg
    SK Snøgg is a Norwegian sports club best known for its football team, which has featured prominent players such as Hege Riise.
  • E. Thunder Snow
    Thunder Snow is a prominent Irish-bred Thoroughbred racehorse best known for winning back-to-back Dubai World Cups in 2018 and 2019.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SNØ
Target entity description: SNØ is a large indoor ski arena in Lørenskog, Norway, offering year-round facilities for alpine skiing, snowboarding, and other winter sports.
  • A. Snoge
    Snoge is the historic 17th-century Portuguese-Israelite synagogue in Amsterdam, renowned as one of the oldest and best-preserved Sephardic synagogues in Europe.
  • B. Sno
    Sno is a small mountain village in northeastern Georgia’s Kazbegi region, known for its traditional stone towers and scenic Caucasus landscapes.
  • C. Snowdown
    Snowdown is a former coal mining village in the Kent coalfield of southeast England, historically centered around Snowdown Colliery and its mining community.
  • D. SK Snøgg
    SK Snøgg is a Norwegian sports club best known for its football team, which has featured prominent players such as Hege Riise.
  • E. Thunder Snow
    Thunder Snow is a prominent Irish-bred Thoroughbred racehorse best known for winning back-to-back Dubai World Cups in 2018 and 2019.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasIndoorSkiArena
Context triple: [Lørenskog municipality, hasIndoorSkiArena, SNØ]
  • A. hasSkiCenter
    Indicates that a location or entity possesses or hosts a ski center as one of its facilities or features.
  • B. hasIceArena
    Indicates that one entity possesses, contains, or includes an ice arena as a facility or feature.
  • C. hasNightSkiing
    Indicates that a location or facility offers skiing activities that take place during nighttime under artificial lighting.
  • D. hasSkiAreaAccess
    Indicates that an entity provides direct access to, or is directly connected with, a ski area or ski facilities.
  • E. hasSnowPark
    Indicates that a location or facility includes or is equipped with a designated snow park area.
  • F. None of above. chosen

Provenance (4 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_69e245884860819081046ce07d5872c4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f167eb08c88190bf2380fa8575d2da completed April 29, 2026, 2:07 a.m.
PD Predicate disambiguation batch_69ee62855558819080da946c7b35a160 completed April 26, 2026, 7:07 p.m.
PDg Predicate description generation batch_69ee8841e9cc81908d23b34215e3be71 completed April 26, 2026, 9:48 p.m.
Created at: April 17, 2026, 2:56 p.m.