Triple

T8043330
Position Surface form Disambiguated ID Type / Status
Subject The Actor E187485 entity
Predicate title P38 FINISHED
Object The Actor E179454 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: The Actor | Statement: [The Actor, title, The Actor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Actor
Context triple: [The Actor, title, The Actor]
  • A. The Actor chosen
    The Actor is the iconic bronze statuette presented to winners of the Screen Actors Guild Awards, symbolizing excellence in film and television acting.
  • B. The Actor
    The Actor was the nickname of Willie Sutton, a notorious American bank robber famed for his elaborate disguises and theatrical methods during heists.
  • C. The Actor
    The Actor is a 1904 painting by Pablo Picasso from his Rose Period, depicting an elegantly costumed figure in a stylized, theatrical pose.
  • D. Being an Actor
    Being an Actor is a book by Simon Callow that offers an insightful, often candid exploration of the craft, profession, and realities of an actor’s life.
  • E. The Actress
    The Actress is a 1953 American comedy-drama film, directed by George Cukor and based on Ruth Gordon’s autobiographical play, depicting a young woman’s determination to pursue a stage career against her father’s wishes.
  • 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_69ca82b00cb48190b59a300f70e97bd7 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f49dcfc81909ac7c93e19ad05c2 completed March 31, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93c407cc81908029bfdd5a0393f1 completed April 1, 2026, 3:40 a.m.
Created at: March 30, 2026, 5:23 p.m.