Triple

T19456225
Position Surface form Disambiguated ID Type / Status
Subject RoboCop (2014 film) E486738 entity
Predicate castMember P1668 FINISHED
Object Joel Kinnaman 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: Joel Kinnaman | Statement: [RoboCop (2014 film), castMember, Joel Kinnaman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joel Kinnaman
Context triple: [RoboCop (2014 film), castMember, Joel Kinnaman]
  • A. Joel Kinnaman chosen
    Joel Kinnaman is a Swedish-American actor known for roles in films like "The Suicide Squad" and series such as "The Killing" and "Altered Carbon."
  • B. Daniel Henney
    Daniel Henney is an American actor and model known for his roles in films and television series such as "Big Hero 6," "Criminal Minds," and "The Wheel of Time."
  • C. Kevin Zegers
    Kevin Zegers is a Canadian actor best known for his early breakout role in the family film "Air Bud" and later appearances in projects like "Transamerica," "Gossip Girl," and "The Mortal Instruments: City of Bones."
  • D. Joe Keery
    Joe Keery is an American actor and musician best known for his role as Steve Harrington in the Netflix series "Stranger Things."
  • E. Garrett Hedlund
    Garrett Hedlund is an American actor and singer known for roles in films such as "Tron: Legacy," "Friday Night Lights," and "Country Strong."
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c4088881908f23f25a82a513f6 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.