Triple

T11572447
Position Surface form Disambiguated ID Type / Status
Subject Catch Me If You Can E274422 entity
Predicate author P4 FINISHED
Object Stan Redding E274422 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: Stan Redding | Statement: [Catch Me If You Can, author, Stan Redding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stan Redding
Context triple: [Catch Me If You Can, author, Stan Redding]
  • A. Stan Redding chosen
    Stan Redding was an American writer best known for co-authoring Frank Abagnale Jr.’s memoir "Catch Me If You Can," which inspired the popular film adaptation.
  • B. Lee Boardman
    Lee Boardman is a British actor known for his roles in television dramas such as Rome and Coronation Street.
  • C. Ritchie Smyth
    Ritchie Smyth is an Irish director best known for his work on high-profile music videos and commercials.
  • D. Ken Boothe
    Ken Boothe is a Jamaican singer renowned for his soulful rocksteady and reggae recordings, including the hit "Everything I Own."
  • E. Billy Sadler
    Billy Sadler is a former professional American football player best known for his time as a standout member of the short-lived World Football League team, the San Antonio Wings.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd6913881908becf188c0a7a275 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e8a776ea40819084912ad2459c5be9 completed April 22, 2026, 10:48 a.m.
Created at: April 8, 2026, 9:38 p.m.