Triple

T19797874
Position Surface form Disambiguated ID Type / Status
Subject Along Came Bialy E475590 entity
Predicate associatedCharacter P12208 FINISHED
Object Little Old Ladies 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: Little Old Ladies | Statement: [Along Came Bialy, associatedCharacter, Little Old Ladies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Little Old Ladies
Context triple: [Along Came Bialy, associatedCharacter, Little Old Ladies]
  • A. The Old Lady
    The Old Lady is a recurring comic character from Fontaine Fox’s early 20th-century newspaper strip "Toonerville Folks," known for embodying the quaint, humorous charm of small-town life.
  • B. My Old Lady
    My Old Lady is a stage play (later adapted into a film) that blends drama and dark comedy as it follows an American man who inherits a Paris apartment occupied by an elderly woman with a complex past.
  • C. "Old Lady"
    "Old Lady" is a colloquial nickname referring to the Bank of England, derived from the famous satirical figure known as the Old Lady of Threadneedle Street.
  • D. The Old People
    "The Old People" is a short story by William Faulkner that forms part of his collection *Go Down, Moses*, exploring themes of heritage, race, and the Southern wilderness through a young boy’s hunting experiences.
  • E. Miss Granny
    Miss Granny is a popular South Korean comedy-drama film about an elderly woman who mysteriously regains her youthful appearance, leading to humorous and heartfelt consequences.
  • 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: Little Old Ladies
Target entity description: Little Old Ladies are a chorus of elderly women in the musical "The Producers," humorously portrayed as enthusiastic backers of Max Bialystock’s theatrical schemes.
  • A. The Old Lady
    The Old Lady is a recurring comic character from Fontaine Fox’s early 20th-century newspaper strip "Toonerville Folks," known for embodying the quaint, humorous charm of small-town life.
  • B. My Old Lady
    My Old Lady is a stage play (later adapted into a film) that blends drama and dark comedy as it follows an American man who inherits a Paris apartment occupied by an elderly woman with a complex past.
  • C. "Old Lady"
    "Old Lady" is a colloquial nickname referring to the Bank of England, derived from the famous satirical figure known as the Old Lady of Threadneedle Street.
  • D. The Old People
    "The Old People" is a short story by William Faulkner that forms part of his collection *Go Down, Moses*, exploring themes of heritage, race, and the Southern wilderness through a young boy’s hunting experiences.
  • E. Miss Granny
    Miss Granny is a popular South Korean comedy-drama film about an elderly woman who mysteriously regains her youthful appearance, leading to humorous and heartfelt consequences.
  • 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c877288190b56ee7eedea710a3 completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.