Triple

T5916607
Position Surface form Disambiguated ID Type / Status
Subject Victor Mature E131595 entity
Predicate name P16 FINISHED
Object Victor Mature E131595 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: Victor Mature | Statement: [Victor Mature, name, Victor Mature]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor Mature
Context triple: [Victor Mature, name, Victor Mature]
  • A. Victor Mature chosen
    Victor Mature was an American film actor known for his rugged leading-man roles in 1940s and 1950s Hollywood epics and adventure films.
  • B. Robert Cummings
    Robert Cummings was an American film and television actor best known for his roles in comedies and thrillers during Hollywood’s Golden Age.
  • C. Dana Andrews
    Dana Andrews was a prominent American film actor of the 1940s and 1950s, best known for his leading roles in classics such as "Laura" and "The Best Years of Our Lives."
  • D. Melvyn Douglas
    Melvyn Douglas was an acclaimed American actor known for his sophisticated screen presence and award-winning performances in both classic Hollywood films and later character roles.
  • E. Edmund Lowe
    Edmund Lowe was an American film actor best known for his leading roles in silent and early sound-era Hollywood films, particularly in war dramas and comedies.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c037bcea9c8190a34dc03857e3b80b completed March 22, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6537678fc8190aa0f2f198c1d8385 completed March 27, 2026, 9:52 a.m.
Created at: March 22, 2026, 3:59 p.m.