Triple

T16191491
Position Surface form Disambiguated ID Type / Status
Subject Mr. Deeds E392951 entity
Predicate producer P490 FINISHED
Object Sidney Ganis E1110172 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: Sidney Ganis | Statement: [Mr. Deeds, producer, Sidney Ganis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sidney Ganis
Context triple: [Mr. Deeds, producer, Sidney Ganis]
  • A. Sidney Ganis chosen
    Sidney Ganis is an American film producer and former president of the Academy of Motion Picture Arts and Sciences known for his work on numerous Hollywood films.
  • B. Charles Guggenheim
    Charles Guggenheim was an American documentary filmmaker renowned for his politically engaged and historically focused films, earning multiple Academy Awards over his career.
  • C. Milton Shifman
    Milton Shifman was a film editor known for his work on mid-20th-century American movies, including adventure films such as "The Sword of Ali Baba."
  • D. Marvin Duchow
    Marvin Duchow was a Canadian musicologist and influential professor of music at McGill University, known for his scholarship in Renaissance and Baroque music.
  • E. Gene Rosow
    Gene Rosow is a film and television producer best known for his work on family-oriented and nature-themed projects such as the movie "Zeus and Roxanne."
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d5769c8190bbb604bfa095a1a5 completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139e380bc81908452f6e8666f23ad completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:02 a.m.