Triple

T7849067
Position Surface form Disambiguated ID Type / Status
Subject Executive Decision E181997 entity
Predicate editedBy P1954 FINISHED
Object Tom Rolf E214378 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: Tom Rolf | Statement: [Executive Decision, editedBy, Tom Rolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Rolf
Context triple: [Executive Decision, editedBy, Tom Rolf]
  • A. Tom Rolf chosen
    Tom Rolf was an American film editor best known for his work on acclaimed movies such as "Taxi Driver" and for winning an Academy Award for editing "The Right Stuff."
  • B. Ron Hagen
    Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
  • C. Duane Schuler
    Duane Schuler is an American theatrical lighting designer known for his work in opera, including major productions at leading opera houses.
  • D. Roy Sievers
    Roy Sievers was an American Major League Baseball first baseman and outfielder known as a powerful slugger of the 1950s, earning multiple All-Star selections and leading the American League in home runs and RBIs during his career.
  • E. Ray Heindorf
    Ray Heindorf was an American composer, arranger, and musical director best known for his work on numerous Hollywood film scores during the mid-20th century.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18e7f5988190808ae4dcfbc06991 completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b0515c08190b866a39749d54849 completed March 31, 2026, 5:26 a.m.
Created at: March 30, 2026, 4:50 p.m.