Triple

T8620798
Position Surface form Disambiguated ID Type / Status
Subject Peter Andrews E204157 entity
Predicate usedInFilm P795 FINISHED
Object Magic Mike E366057 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: Magic Mike | Statement: [Peter Andrews, usedInFilm, Magic Mike]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magic Mike
Context triple: [Peter Andrews, usedInFilm, Magic Mike]
  • A. Magic Mike chosen
    Magic Mike is a 2012 comedy-drama film about male strippers, directed by Steven Soderbergh and starring Channing Tatum and Matthew McConaughey.
  • B. Magic Mike XXL
    Magic Mike XXL is a 2015 comedy-drama film that follows a group of male strippers on a road trip to a stripper convention, serving as the sequel to the film Magic Mike.
  • C. Side Show
    Side Show is a Broadway musical by composer Henry Krieger that dramatizes the lives of conjoined twins Daisy and Violet Hilton in the world of 1930s sideshow entertainment.
  • D. Like Mike
    Like Mike is a 2002 family sports comedy film about an orphan who gains extraordinary basketball skills after wearing a pair of magical sneakers.
  • E. Don Jon
    Don Jon is a 2013 romantic comedy-drama film written and directed by Joseph Gordon-Levitt, following a New Jersey man's struggle to balance his porn addiction with real-life relationships.
  • 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_69ca832ceab8819096e4a9f546695079 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc47167b188190b5d9a113db9b9511 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbdd6aac819091f6dd12815c3d94 completed April 2, 2026, 6:56 p.m.
Created at: March 30, 2026, 6:26 p.m.