Triple

T345788
Position Surface form Disambiguated ID Type / Status
Subject Ralph Nelson E6938 entity
Predicate name P16 FINISHED
Object Ralph Nelson E6938 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: Ralph Nelson | Statement: [Ralph Nelson, name, Ralph Nelson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ralph Nelson
Context triple: [Ralph Nelson, name, Ralph Nelson]
  • A. Ralph Nelson chosen
    Ralph Nelson was an American film and television director, producer, and writer known for works such as "Lilies of the Field" and "Requiem for a Heavyweight."
  • B. 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.
  • C. Louis Calhern
    Louis Calhern was an American stage and film actor known for his sophisticated character roles in classic Hollywood cinema, including notable performances in films like "The Asphalt Jungle" and "Julius Caesar."
  • 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. David Wayne
    David Wayne was an American character actor known for his versatile performances in film, television, and theater from the 1940s through the 1980s.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb0240e88190bc70784772f5fa30 completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d7eb6b708190b0dff991c101104f completed March 1, 2026, 6:08 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.