Triple

T14644885
Position Surface form Disambiguated ID Type / Status
Subject 9 to 5 E343819 entity
Predicate starring P1507 FINISHED
Object Sterling Hayden E20817 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: Sterling Hayden | Statement: [9 to 5, starring, Sterling Hayden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sterling Hayden
Context triple: [9 to 5, starring, Sterling Hayden]
  • A. Sterling Hayden chosen
    Sterling Hayden was an American actor and World War II hero known for his rugged film roles and his clandestine service as a Marine and OSS operative.
  • B. Eddie Bracken
    Eddie Bracken was an American comedic actor known for his roles in 1940s and 1950s film comedies and Broadway productions.
  • C. Richard Basehart
    Richard Basehart was an American actor known for his versatile film and television roles, including performances in "La Strada" and the TV series "Voyage to the Bottom of the Sea."
  • D. Herbert Reynolds
    Herbert Reynolds was an early 20th-century American lyricist best known for his collaborations with composer Jerome Kern on popular songs from the musical theatre and Tin Pan Alley era.
  • E. Zachary Scott
    Zachary Scott was an American actor best known for his suave yet often villainous roles in 1940s and 1950s Hollywood films.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0035428e608190b8bb41dabda044d1 completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 1:26 a.m.