Triple

T16229253
Position Surface form Disambiguated ID Type / Status
Subject Virtuosity E393935 entity
Predicate screenwriter P2831 FINISHED
Object Eric Bernt E595298 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: Eric Bernt | Statement: [Virtuosity, screenwriter, Eric Bernt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eric Bernt
Context triple: [Virtuosity, screenwriter, Eric Bernt]
  • A. Eric Bernt chosen
    Eric Bernt is an American screenwriter known for his work on action and thriller films, including the 2000 martial arts crime movie "Romeo Must Die."
  • B. Eric Bernthal
    Eric Bernthal is an American lawyer and former chair of the Humane Society of the United States, best known as the father of actor Jon Bernthal.
  • C. Eric Bergstol
    Eric Bergstol is an American golf course architect known for designing high-end, links-style courses in the New York metropolitan area.
  • D. Erik Josten
    Erik Josten is a Marvel Comics supervillain-turned-antihero known for his immense strength and size-changing powers under various aliases, including Power Man, Goliath, and Atlas.
  • E. Eric Sigler
    Eric Sigler is a researcher known for co-authoring influential work in artificial intelligence and machine learning alongside Tom B. Brown.
  • 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e23d2889688190ac04e4e9479cabf4 completed April 17, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017ab10a48190afa19e74c0059427 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:03 a.m.