Triple

T3422593
Position Surface form Disambiguated ID Type / Status
Subject Morning Glory (1933 film) E72147 entity
Predicate screenwriter P2831 FINISHED
Object 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.
 E400857 NE FINISHED

How this triple was built (4 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 J. Green | Statement: [Morning Glory (1933 film), screenwriter, Howard J. Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Howard J. Green
Context triple: [Morning Glory (1933 film), screenwriter, Howard J. Green]
  • A. Bernard L. Green
    Bernard L. Green was an architect known for designing the building known as The Big House.
  • B. Gerald B. Greenberg
    Gerald B. Greenberg is an American film editor best known for his Academy Award–winning work on the 1979 drama "Kramer vs. Kramer."
  • C. Andrew H. Green
    Andrew H. Green was a prominent New York civic leader and urban planner known for helping shape Central Park and other major city institutions in the 19th century.
  • D. Howard Green
    Howard Green was a Canadian politician who served as the country's Secretary of State for External Affairs in the mid-20th century.
  • E. George A. Bermann
    George A. Bermann is a prominent American legal scholar and expert in international and comparative law, particularly known for his work in international arbitration.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Howard J. Green
Triple: [Morning Glory (1933 film), screenwriter, Howard J. Green]
Generated description
Howard J. Green was an American screenwriter active during Hollywood’s early sound era, known for his work on several prominent 1930s films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Howard J. Green
Target entity description: Howard J. Green was an American screenwriter active during Hollywood’s early sound era, known for his work on several prominent 1930s films.
  • A. Bernard L. Green
    Bernard L. Green was an architect known for designing the building known as The Big House.
  • B. Gerald B. Greenberg
    Gerald B. Greenberg is an American film editor best known for his Academy Award–winning work on the 1979 drama "Kramer vs. Kramer."
  • C. Andrew H. Green
    Andrew H. Green was a prominent New York civic leader and urban planner known for helping shape Central Park and other major city institutions in the 19th century.
  • D. Howard Green
    Howard Green was a Canadian politician who served as the country's Secretary of State for External Affairs in the mid-20th century.
  • E. George A. Bermann
    George A. Bermann is a prominent American legal scholar and expert in international and comparative law, particularly known for his work in international arbitration.
  • F. None of above. chosen

Provenance (5 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb95223e081908b2954769d2f46c8 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5335e1e348190912455cd90009558 completed March 14, 2026, 10:07 a.m.
NEDg Description generation batch_69b533e758e481909405ca6bf48ba756 completed March 14, 2026, 10:09 a.m.
NED2 Entity disambiguation (via description) batch_69b5345d7098819087ba99920e0ad990 completed March 14, 2026, 10:11 a.m.
Created at: March 8, 2026, 3:15 p.m.