Triple

T11941228
Position Surface form Disambiguated ID Type / Status
Subject The Hazards of Helen E284181 entity
Predicate mainCharacterName P29319 FINISHED
Object Helen
Helen is the daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
E955123 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: [The Hazards of Helen, mainCharacterName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [The Hazards of Helen, mainCharacterName, 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 a central character in Ernest Hemingway’s short story “The Snows of Kilimanjaro,” portrayed as the wealthy, devoted wife and companion of the writer Harry during his final, reflective days in Africa.
  • D. Helen
    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.
  • E. Helen
    Helen is a person characterized in this context by her adversarial relationship with Deacon.
  • 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: [The Hazards of Helen, mainCharacterName, Helen]
Generated description
Helen is the daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen
Target entity description: Helen is the daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
  • A. Helen
    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 fictional protagonist associated with a narrative set in or around New York City's Central Park.
  • D. Helen
    Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
  • E. Helen
    Helen is a person characterized in this context by her adversarial relationship with Deacon.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90342bb908190a019ac91a2b82f3d completed April 10, 2026, 2:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f440a5a9c8819086a94ad60c6881b8 completed May 1, 2026, 5:56 a.m.
NEDg Description generation batch_69f448fd4b908190a4f08619d346bec8 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44b08da6c8190ae62d8e892bf1971 completed May 1, 2026, 6:41 a.m.
Created at: April 8, 2026, 9:45 p.m.