Triple

T17606905
Position Surface form Disambiguated ID Type / Status
Subject The Professionals E428855 entity
Predicate starring P1507 FINISHED
Object Robert Ryan 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: Robert Ryan | Statement: [The Professionals, starring, Robert Ryan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Ryan
Context triple: [The Professionals, starring, Robert Ryan]
  • A. Robert Ryan chosen
    Robert Ryan was an American actor renowned for his intense portrayals of tough, complex characters in mid-20th-century film noir and drama.
  • B. Richard Farnsworth
    Richard Farnsworth was an American actor and former stuntman best known for his understated, dignified performances in films such as "The Straight Story" and "Comes a Horseman."
  • C. Aldo Ray
    Aldo Ray was an American film actor known for his tough-guy roles and distinctive raspy voice in numerous Hollywood movies of the 1950s and 1960s.
  • D. Lee Marvin
    Lee Marvin was an American film and television actor known for his tough-guy roles in war movies and Westerns, including his Oscar-winning performance in "Cat Ballou."
  • E. Dan Duryea
    Dan Duryea was an American character actor best known for his distinctive portrayals of sneering villains and tough guys in film noir and classic Hollywood movies of the 1940s and 1950s.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c4ccef08190aeaa88670364bd74 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.