Triple

T5043713
Position Surface form Disambiguated ID Type / Status
Subject The Killing (1956 film) E113608 entity
Predicate castMember P1668 FINISHED
Object Ted de Corsia E490154 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: Ted de Corsia | Statement: [The Killing (1956 film), castMember, Ted de Corsia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ted de Corsia
Context triple: [The Killing (1956 film), castMember, Ted de Corsia]
  • A. Ted de Corsia chosen
    Ted de Corsia was an American character actor known for his tough-guy roles in classic film noir and crime movies of the mid-20th century.
  • B. Greg Corrado
    Greg Corrado is an American computer scientist and researcher known for his pioneering work in artificial intelligence and deep learning, including co-founding Google Brain.
  • C. Greg D'Auria
    Greg D'Auria is a film editor known for his work on major Hollywood productions, including the science fiction film "Star Trek Beyond."
  • D. Roger de Lauria
    Roger de Lauria was a renowned 13th-century admiral of the Crown of Aragon, celebrated for his decisive naval victories in the Mediterranean during the War of the Sicilian Vespers.
  • E. Michael D’Orso
    Michael D’Orso is an American author and journalist known for co-writing influential nonfiction books, often chronicling social justice movements and notable public figures.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73fc04f08190aba851fa0192d0fb completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee06486c481908e11dc53875ee31b completed March 21, 2026, 6:16 p.m.
Created at: March 20, 2026, 1:37 p.m.