Triple

T13338511
Position Surface form Disambiguated ID Type / Status
Subject The President’s Lady E317760 entity
Predicate producer P490 FINISHED
Object Sol C. Siegel E64842 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: Sol C. Siegel | Statement: [The President’s Lady, producer, Sol C. Siegel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sol C. Siegel
Context triple: [The President’s Lady, producer, Sol C. Siegel]
  • A. Sol C. Siegel chosen
    Sol C. Siegel was an American film producer known for overseeing numerous major Hollywood productions from the 1940s through the 1960s.
  • B. J. David Siegel
    J. David Siegel is a film editor known for his work on major animated features, including the superhero comedy "DC League of Super-Pets."
  • C. Steven Fierberg
    Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
  • D. Ian Siegel
    Ian Siegel is an American entrepreneur best known as the co-founder and longtime CEO of the online employment marketplace ZipRecruiter.
  • E. William Sheinberg
    William Sheinberg is known primarily as the son of influential Hollywood executive Sidney Sheinberg.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99d01bf8481908cd3a99e5557b972 completed April 11, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002d92c9788190aa4523a1e47bc561 completed May 10, 2026, 7:02 a.m.
Created at: April 9, 2026, 9:31 p.m.