Triple

T8982410
Position Surface form Disambiguated ID Type / Status
Subject Howard Green E214563 entity
Predicate name P16 FINISHED
Object Howard Charles Green E214563 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: Howard Charles Green | Statement: [Howard Green, name, Howard Charles Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Charles Green
Context triple: [Howard Green, name, Howard Charles Green]
  • A. Howard Green chosen
    Howard Green was a Canadian politician who served as the country's Secretary of State for External Affairs in the mid-20th century.
  • B. Howard J. Green
    Howard J. Green was an American screenwriter active during Hollywood’s early sound era, known for his work on several prominent 1930s films.
  • C. Herbert Greene
    Herbert Greene was an American Broadway conductor and musical director best known for his work on classic mid-20th-century stage productions.
  • D. Howard Greenhalgh
    Howard Greenhalgh is a British music video director known for his visually distinctive and often surreal work for major rock and pop artists in the 1990s and beyond.
  • E. Christopher Greenbury
    Christopher Greenbury was a British film editor best known for his Academy Award–winning work on the 1999 drama "American Beauty."
  • 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_69ca839ea8b88190922c6a326ffcc0d3 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc67a891e881909e4b84ed82491651 completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc97617908190859d1e27248f43cf completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:03 p.m.