Triple

T7498436
Position Surface form Disambiguated ID Type / Status
Subject Palooka E177193 entity
Predicate starring P1507 FINISHED
Object Stuart Erwin E162416 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: Stuart Erwin | Statement: [Palooka, starring, Stuart Erwin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stuart Erwin
Context triple: [Palooka, starring, Stuart Erwin]
  • A. Stuart Erwin chosen
    Stuart Erwin was an American actor known for his work in early 20th-century film, radio, and television, often portraying affable, comedic everyman characters.
  • B. Victor Mature
    Victor Mature was an American film actor known for his rugged leading-man roles in 1940s and 1950s Hollywood epics and adventure films.
  • C. Rance Howard
    Rance Howard was an American character actor known for his extensive work in film and television and as the patriarch of the Howard acting and directing family.
  • D. Roy Harlow
    Roy Harlow was the husband of silent film actress Marie Mosquini, known primarily in relation to her career in early American cinema.
  • E. Robert Montgomery
    Robert Montgomery was an American film and television actor and director prominent in the 1930s and 1940s, known for his roles in both light comedies and dramas as well as his later work behind the camera.
  • 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f597a0c08190b34fa283a11d98c7 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856acc3208190985e10c285f41e02 completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:44 p.m.