Triple

T8801255
Position Surface form Disambiguated ID Type / Status
Subject Philip Seymour Hoffman as Freddie Miles E209412 entity
Predicate basedOnAuthor P2806 FINISHED
Object Patricia Highsmith E209408 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: Patricia Highsmith | Statement: [Philip Seymour Hoffman as Freddie Miles, basedOnAuthor, Patricia Highsmith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patricia Highsmith
Context triple: [Philip Seymour Hoffman as Freddie Miles, basedOnAuthor, Patricia Highsmith]
  • A. Patricia Highsmith chosen
    Patricia Highsmith was an American novelist best known for her psychologically complex crime and suspense fiction, including the Ripley series.
  • B. Sally Kellerman
    Sally Kellerman was an American actress and singer best known for her Oscar-nominated role as Major Margaret "Hot Lips" Houlihan in the film MASH.
  • C. Mary Higgins Clark
    Mary Higgins Clark was a bestselling American author renowned for her suspenseful mystery and thriller novels, often featuring strong female protagonists.
  • D. Sue Grafton
    Sue Grafton was an American mystery writer best known for her alphabet-titled Kinsey Millhone detective novels.
  • E. Paula Hawkins
    Paula Hawkins is a British author best known for her psychological thriller novel "The Girl on the Train," which was adapted into the 2016 film of the same name.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fb9c5c88190881b069e1face10c completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfab60ee608190af9f4aba631b42ef completed April 3, 2026, 11:58 a.m.
Created at: March 30, 2026, 6:44 p.m.