Triple

T22008787
Position Surface form Disambiguated ID Type / Status
Subject Kerli Kõiv E543519 entity
Predicate hasCollaboratedWith P8554 FINISHED
Object Tokio Hotel 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: Tokio Hotel | Statement: [Kerli Kõiv, hasCollaboratedWith, Tokio Hotel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokio Hotel
Context triple: [Kerli Kõiv, hasCollaboratedWith, Tokio Hotel]
  • A. Tokio Hotel chosen
    Tokio Hotel is a German pop-rock band that gained international fame in the mid-2000s with hits like "Monsoon" and a distinctive emo-inspired image.
  • B. The Rasmus
    The Rasmus is a Finnish rock band best known internationally for their 2003 hit single "In the Shadows."
  • C. The Coronas
    The Coronas are an Irish rock band known for their melodic, radio-friendly sound and success on the Irish music charts.
  • D. The Cardigans
    The Cardigans are a Swedish rock band best known internationally for their 1990s hits like "Lovefool," blending catchy pop melodies with alternative rock influences.
  • E. Danjaq
    Danjaq is the film production and rights-holding company best known for owning and controlling the James Bond movie franchise.
  • 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_69e11e2db934819095556760c7d85e4d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127a2aebc8190951ee0bf9fd8e16d completed April 28, 2026, 9:33 p.m.
Created at: April 16, 2026, 8:21 p.m.