Triple

T21335508
Position Surface form Disambiguated ID Type / Status
Subject Kitty Carlisle E526034 entity
Predicate notableWork P4 FINISHED
Object She Loves Me NE NERFINISHED

How this triple was built (2 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: She Loves Me | Statement: [Kitty Carlisle, notableWork, She Loves Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: She Loves Me
Context triple: [Kitty Carlisle, notableWork, She Loves Me]
  • A. She Loves Me chosen
    She Loves Me is a classic 1963 Broadway musical romantic comedy, with music by Jerry Bock and lyrics by Sheldon Harnick, adapted from the play "Parfumerie" by Miklós László.
  • B. Kiss Me, Kate
    Kiss Me, Kate is a classic Broadway musical comedy by Cole Porter that playfully intertwines a backstage romance with a musical adaptation of Shakespeare’s The Taming of the Shrew.
  • C. Prima Donna
    Prima Donna is an American rock band known for its glam-punk style and energetic live performances.
  • D. The Merry Widow
    The Merry Widow is a 1925 silent romantic drama film directed by Erich von Stroheim, celebrated for its lavish production, darkly comic tone, and influence on early Hollywood cinema.
  • E. The Most Happy Fella
    The Most Happy Fella is a 1956 Broadway musical by Frank Loesser, known for its operatic score and romantic story set in California’s Napa Valley.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69e0b51c33048190ab27cede74ef798c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e898d6fcbc8190b83d9cfc9b4ca123 completed April 22, 2026, 9:45 a.m.
Created at: April 16, 2026, 4:43 p.m.