Triple

T9837047
Position Surface form Disambiguated ID Type / Status
Subject Honor Among Lovers E239127 entity
Predicate editor P1954 FINISHED
Object Helene Turner
Helene Turner was a film editor active during the early 20th century, known for her work on American feature films.
 E911079 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: Helene Turner | Statement: [Honor Among Lovers, editor, Helene Turner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Helene Turner
Context triple: [Honor Among Lovers, editor, Helene Turner]
  • A. Helene Bradley
    Helene Bradley is a fictional character appearing in Ernest Hemingway’s novel "To Have and Have Not."
  • B. Helen Vinson
    Helen Vinson was an American film actress of the 1930s and 1940s, often cast in sophisticated or morally ambiguous roles in Hollywood dramas and crime films.
  • C. Helene Wright
    Helene Wright is a character in Toni Morrison’s novel "Song of Solomon," known as the devoutly religious and socially proper mother of Milkman (Nel) Wright.
  • D. Helen Wright
    Helen Wright is a wealthy, emotionally volatile socialite who becomes romantically entangled with a young violin prodigy in the film "Humoresque."
  • E. Helen Brown
    Helen Brown is an actress known for her role in the classic "The Twilight Zone" episode "Walking Distance."
  • 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: Helene Turner
Triple: [Honor Among Lovers, editor, Helene Turner]
Generated description
Helene Turner was a film editor active during the early 20th century, known for her work on American feature films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Helene Turner
Target entity description: Helene Turner was a film editor active during the early 20th century, known for her work on American feature films.
  • A. Helene Bradley
    Helene Bradley is a fictional character appearing in Ernest Hemingway’s novel "To Have and Have Not."
  • B. Helen Vinson
    Helen Vinson was an American film actress of the 1930s and 1940s, often cast in sophisticated or morally ambiguous roles in Hollywood dramas and crime films.
  • C. Helene Wright
    Helene Wright is a character in Toni Morrison’s novel "Song of Solomon," known as the devoutly religious and socially proper mother of Milkman (Nel) Wright.
  • D. Helen Wright
    Helen Wright is a wealthy, emotionally volatile socialite who becomes romantically entangled with a young violin prodigy in the film "Humoresque."
  • E. Helen Brown
    Helen Brown is an actress known for her role in the classic "The Twilight Zone" episode "Walking Distance."
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb33b07688190b78a70cf535c3efc completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4963545f481909ecc360480b1fc37 completed April 19, 2026, 8:45 a.m.
NEDg Description generation batch_69e49a97db808190aa22d6a103a13e58 completed April 19, 2026, 9:04 a.m.
NED2 Entity disambiguation (via description) batch_69e49d71e81c8190af73931ed30e04be completed April 19, 2026, 9:16 a.m.
Created at: March 30, 2026, 8:33 p.m.