Triple

T22663390
Position Surface form Disambiguated ID Type / Status
Subject Piya Tu Ab To Aaja E559719 entity
Predicate picturizedOn P50414 FINISHED
Object Helen
Helen is an iconic Indian film actress and dancer, celebrated as Bollywood’s most famous cabaret star from the 1950s through the 1970s.
E1548596 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: [Piya Tu Ab To Aaja, picturizedOn, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Piya Tu Ab To Aaja, picturizedOn, 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: [Piya Tu Ab To Aaja, picturizedOn, Helen]
Generated description
Helen is an iconic Indian film actress and dancer, celebrated as Bollywood’s most famous cabaret star from the 1950s through the 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen
Target entity description: Helen is an iconic Indian film actress and dancer, celebrated as Bollywood’s most famous cabaret star from the 1950s through the 1970s.
  • A. Helen chosen
    Helen was a legendary Bollywood dancer and actress, famed for her iconic cabaret and vamp roles in Hindi cinema from the 1950s to the 1970s.
  • B. Helen
    Helen is the given name of Lady Helen Taylor, a British aristocrat and member of the extended royal family known for her work in the arts and fashion.
  • C. 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.
  • D. Helen
    Helen is a Greek and Danish princess of the early 20th century, known as Princess Helen of Greece and Denmark.
  • E. 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.
  • 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_69e2454a158c819093b8e35f5045efb6 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f176617ed8819095a58a2c9f1e3918 completed April 29, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b7ec593f0819081a3f8e56a9f1e1f completed May 18, 2026, 9:04 p.m.
NEDg Description generation batch_6a0b803e725081908e23dbe3da3622ab completed May 18, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_6a0b80e09d2081908400cc978d76a4a1 completed May 18, 2026, 9:13 p.m.
Created at: April 17, 2026, 3:08 p.m.