Triple

T18686122
Position Surface form Disambiguated ID Type / Status
Subject Lauren Kelly E456867 entity
Predicate notableWork P4 FINISHED
Object Two Girls, Fat and Thin NE NERFINISHED

How this triple was built (3 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: Two Girls, Fat and Thin | Statement: [Lauren Kelly, notableWork, Two Girls, Fat and Thin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Two Girls, Fat and Thin
Context triple: [Lauren Kelly, notableWork, Two Girls, Fat and Thin]
  • A. Two Girls
    "Two Girls" is a figurative painting by American artist Isabel Bishop, exemplifying her nuanced depictions of everyday urban women in mid-20th-century New York.
  • B. The Little Girls
    The Little Girls is a 1964 novel by Elizabeth Bowen that explores memory, aging, and the lingering impact of childhood through the reunion of three former schoolfriends.
  • C. Two Little Girls in Blue
    Two Little Girls in Blue is a 1921 Broadway musical comedy with music by Vincent Youmans, known as one of his early successes in American musical theatre.
  • D. Two Little Girls in Blue
    Two Little Girls in Blue is a suspense novel by Mary Higgins Clark that follows the mysterious kidnapping of toddler twins and their telepathic bond that helps unravel the crime.
  • E. Three Girls
    Three Girls is a British television drama miniseries based on the real-life Rochdale child grooming scandal, acclaimed for its powerful performances and sensitive handling of the subject matter.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Two Girls, Fat and Thin
Target entity description: Two Girls, Fat and Thin is a darkly comic literary novel by Mary Gaitskill that explores female friendship, trauma, and power dynamics through the intertwined lives of two very different women.
  • A. Two Girls
    "Two Girls" is a figurative painting by American artist Isabel Bishop, exemplifying her nuanced depictions of everyday urban women in mid-20th-century New York.
  • B. The Little Girls
    The Little Girls is a 1964 novel by Elizabeth Bowen that explores memory, aging, and the lingering impact of childhood through the reunion of three former schoolfriends.
  • C. Two Little Girls in Blue
    Two Little Girls in Blue is a 1921 Broadway musical comedy with music by Vincent Youmans, known as one of his early successes in American musical theatre.
  • D. Two Little Girls in Blue
    Two Little Girls in Blue is a suspense novel by Mary Higgins Clark that follows the mysterious kidnapping of toddler twins and their telepathic bond that helps unravel the crime.
  • E. Three Girls
    Three Girls is a British television drama miniseries based on the real-life Rochdale child grooming scandal, acclaimed for its powerful performances and sensitive handling of the subject matter.
  • F. None of above. chosen

Provenance (2 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b2c58188190b906c9ab080a76ff completed April 19, 2026, 10:46 p.m.
Created at: April 10, 2026, 11:49 a.m.