Triple

T18093547
Position Surface form Disambiguated ID Type / Status
Subject Bram Stoker's Dracula E433028 entity
Predicate producer P490 FINISHED
Object Fred Fuchs NE NERFINISHED

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: Fred Fuchs | Statement: [Bram Stoker's Dracula, producer, Fred Fuchs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fred Fuchs
Context triple: [Bram Stoker's Dracula, producer, Fred Fuchs]
  • A. Fred Fuchs chosen
    Fred Fuchs is a film and television producer known for his work on projects such as the crime drama film "The Cotton Club."
  • B. Fred F. Finklehoffe
    Fred F. Finklehoffe was an American screenwriter and producer best known for his work on classic Hollywood films and collaborations with major studios during the 1940s.
  • C. Thomas Fuchs
    Thomas Fuchs is a German computer scientist and software developer best known for creating the JavaScript libraries script.aculo.us and contributing to Prototype.
  • D. George Bruns
    George Bruns was an American composer and arranger best known for his work on numerous Disney films and theme park attractions, including iconic scores for animated classics and rides.
  • E. Grant Rosenmeyer
    Grant Rosenmeyer is an American actor best known for his childhood role in Wes Anderson’s film "The Royal Tenenbaums" and later work in independent films and television.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd1a75048190924ebc01da83851b completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.