Triple

T9759468
Position Surface form Disambiguated ID Type / Status
Subject Fanny (1961 film) E236632 entity
Predicate editedBy P1954 FINISHED
Object William Reynolds E366621 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: William Reynolds | Statement: [Fanny (1961 film), editedBy, William Reynolds]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Reynolds
Context triple: [Fanny (1961 film), editedBy, William Reynolds]
  • A. William Reynolds
    William Reynolds is a film editor best known for his work on the classic crime drama "The Godfather."
  • B. William Reynolds
    William Reynolds was an American film and television actor known for his supporting roles in 1950s melodramas and later for co-starring in the TV series "The F.B.I."
  • C. William Reynolds chosen
    William Reynolds is a film editor known for his work on the 1960 adventure drama "Wild River."
  • D. William Reynolds
    William Reynolds was the brother of Union Major General John F. Reynolds, a prominent officer in the American Civil War.
  • E. David Reynolds
    David Reynolds is an American screenwriter best known for his work on acclaimed animated films such as Pixar's "Finding Nemo."
  • 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_69ca84d64f6c8190a4ed4e9f5936eda5 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda049995c81908569ec61805642b2 completed April 1, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d23cd89d1c8190aedab60e3f5088b3 completed April 5, 2026, 10:43 a.m.
Created at: March 30, 2026, 8:24 p.m.