Triple

T13673320
Position Surface form Disambiguated ID Type / Status
Subject Places E327806 entity
Predicate producer P490 FINISHED
Object Kristian Lundin E542318 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: Kristian Lundin | Statement: [Places, producer, Kristian Lundin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristian Lundin
Context triple: [Places, producer, Kristian Lundin]
  • A. Kristian Lundin chosen
    Kristian Lundin is a Swedish songwriter and producer known for crafting late-1990s and early-2000s pop hits for artists such as Backstreet Boys, *NSYNC, and Celine Dion.
  • B. Fredrik Ljungdahl
    Fredrik Ljungdahl is a video game designer known for his work on the first-person shooter Wolfenstein II: The New Colossus.
  • C. Christopher Akerlind
    Christopher Akerlind is an American lighting designer renowned for his work in theatre, opera, and Broadway productions, including multiple award-winning designs.
  • D. Daniel Nannskog
    Daniel Nannskog is a retired Swedish striker best known for his prolific goal-scoring spell at Norwegian club Stabæk Fotball and later work as a football pundit.
  • E. Erik Edlund
    Erik Edlund was a Swedish physicist and academic who mentored future Nobel laureate Svante Arrhenius and contributed to 19th-century physical science education in Sweden.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65aab348190a6611f5765f8392d completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd19259070819089bd3caf66e5af29 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 9:53 p.m.