Triple

T14818739
Position Surface form Disambiguated ID Type / Status
Subject Ørestad E348386 entity
Predicate hasLandmark P105 FINISHED
Object Bella Center E339943 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: Bella Center | Statement: [Ørestad, hasLandmark, Bella Center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bella Center
Context triple: [Ørestad, hasLandmark, Bella Center]
  • A. Bella Center chosen
    Bella Center is a major convention and exhibition center in Copenhagen, Denmark, known for hosting large international conferences, trade fairs, and events.
  • B. Skagerak Arena
    Skagerak Arena is a football stadium in Skien, Norway, best known as the home ground of the club Odds BK.
  • C. Oslo Spektrum
    Oslo Spektrum is a large indoor arena in Oslo, Norway, primarily used for ice hockey, concerts, and major cultural and sporting events.
  • D. Scandinavium arena
    Scandinavium arena is a major indoor sports and entertainment venue in Gothenburg, Sweden, known for hosting ice hockey, concerts, and international events.
  • E. Ballerup Super Arena
    Ballerup Super Arena is a large indoor velodrome and multi-purpose sports and events venue located in Ballerup, Denmark.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe4cf38819090f25ef045351d5d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe389940e081908ad627955cb8d52e completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:50 a.m.