Triple

T11447883
Position Surface form Disambiguated ID Type / Status
Subject Hell's Angels E271310 entity
Predicate featuresCharacter P626 FINISHED
Object Helen
Helen is a character in the 1930 aviation war film "Hell's Angels," which is known for its groundbreaking aerial combat sequences and early use of sound in cinema.
E824714 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: Helen | Statement: [Hell's Angels, featuresCharacter, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Hell's Angels, featuresCharacter, Helen]
  • A. Helen
    Helen is a central survivor and maternal figure in the post-apocalyptic film "Waterworld," known for her determination to protect the child Enola and seek the mythical Dryland.
  • B. Helen
    Helen is the birth name of P. L. Travers, the Australian-British author best known for creating the "Mary Poppins" series.
  • C. Helen
    Helen is the given first name of New Zealand actress Pat Evison, known for her work in film, television, and theatre.
  • D. Helen
    Helen is the central character in the novel "The Spare Room," around whom the story’s emotional and narrative developments revolve.
  • E. Helen
    Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
  • 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: Helen
Triple: [Hell's Angels, featuresCharacter, Helen]
Generated description
Helen is a character in the 1930 aviation war film "Hell's Angels," which is known for its groundbreaking aerial combat sequences and early use of sound in cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen
Target entity description: Helen is a character in the 1930 aviation war film "Hell's Angels," which is known for its groundbreaking aerial combat sequences and early use of sound in cinema.
  • A. Helen chosen
    Helen is a fictional character from the 1930 aviation war film "Hell's Angels," which is renowned for its groundbreaking aerial combat sequences and early sound-era spectacle.
  • B. Helen
    Helen is the mute, terrorized heroine of the classic 1946 psychological thriller film "The Spiral Staircase."
  • C. Helen
    Helen is a character in Aldous Huxley’s novel "Eyeless in Gaza," representing one of the key figures in the book’s exploration of memory, morality, and personal transformation.
  • D. Helen
    Helen is the given first name of New Zealand actress Pat Evison, known for her work in film, television, and theatre.
  • E. Helen
    Helen is a fictional protagonist associated with a narrative set in or around New York City's Central Park.
  • F. None of above.

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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c6d4890819082fb4a670feb2629 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d3cb63408190a96b97f716d46082 completed April 20, 2026, 7:20 a.m.
NEDg Description generation batch_69e5d7e46e248190aba139dc32185e2f completed April 20, 2026, 7:38 a.m.
NED2 Entity disambiguation (via description) batch_69e5e192297c8190992578f734e63427 completed April 20, 2026, 8:19 a.m.
Created at: April 8, 2026, 9:35 p.m.