Triple

T2613595
Position Surface form Disambiguated ID Type / Status
Subject Samuel Goldwyn E58833 entity
Predicate alsoKnownAs P39 FINISHED
Object Sam Goldwyn E58833 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: Sam Goldwyn | Statement: [Samuel Goldwyn, alsoKnownAs, Sam Goldwyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sam Goldwyn
Context triple: [Samuel Goldwyn, alsoKnownAs, Sam Goldwyn]
  • A. Samuel Goldwyn chosen
    Samuel Goldwyn was a pioneering American film producer and studio executive who played a key role in shaping Hollywood’s early motion picture industry.
  • B. Louis B. Mayer
    Louis B. Mayer was a powerful Hollywood film producer and studio executive who co-founded Metro-Goldwyn-Mayer (MGM) and became one of the most influential figures of the studio era.
  • C. Jesse L. Lasky Jr.
    Jesse L. Lasky Jr. was an American screenwriter known for his work on major Hollywood epics and adventure films in the mid-20th century.
  • D. Jesse L. Lasky
    Jesse L. Lasky was a pioneering American film producer and co-founder of Paramount Pictures who played a key role in the development of early Hollywood cinema.
  • E. Walter Wanger
    Walter Wanger was an American film producer known for his work on numerous influential Hollywood films from the 1930s through the 1950s, often tackling socially conscious and ambitious subjects.
  • 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_69ab4ac444dc819099614e534dd6021f completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd87dcfbc8190b264062002bfe4ba completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe88781ec8190a13784501208c5a5 completed March 10, 2026, 9:46 a.m.
Created at: March 6, 2026, 9:50 p.m.