Triple

T5417524
Position Surface form Disambiguated ID Type / Status
Subject Carry On Loving E121167 entity
Predicate producer P490 FINISHED
Object Peter Rogers E521829 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: Peter Rogers | Statement: [Carry On Loving, producer, Peter Rogers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Rogers
Context triple: [Carry On Loving, producer, Peter Rogers]
  • A. Peter Rogers chosen
    Peter Rogers was a British film producer best known for overseeing the long-running and popular "Carry On" comedy film series.
  • B. Paul Rogers
    Paul Rogers is an American film editor best known for his Academy Award–winning work on the multiverse film "Everything Everywhere All at Once."
  • C. Graham Rogers
    Graham Rogers is an American actor known for his roles in television series such as "The Kominsky Method," "Quantico," and "Atypical."
  • D. Ben Rogers
    Ben Rogers is a lively, boastful boy in Mark Twain’s "The Adventures of Tom Sawyer," known for being one of Tom’s close companions in their childhood adventures.
  • E. Howard Emmett Rogers
    Howard Emmett Rogers was an American screenwriter active during Hollywood’s early studio era, known for contributing to several notable films in the 1930s and 1940s.
  • 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_69bd463a41cc8190b32ff5af2b96ca93 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87e620f081909eb9a5e1f284e5a2 completed March 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfc018410c8190bfd0138ced6c2151 completed March 22, 2026, 10:10 a.m.
Created at: March 20, 2026, 2:05 p.m.