Triple

T8851708
Position Surface form Disambiguated ID Type / Status
Subject Bernadette Peters E210652 entity
Predicate notableWork P4 FINISHED
Object Mack & Mabel E500798 NE FINISHED

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: Mack & Mabel | Statement: [Bernadette Peters, notableWork, Mack & Mabel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mack & Mabel
Context triple: [Bernadette Peters, notableWork, Mack & Mabel]
  • A. Mack & Mabel chosen
    Mack & Mabel is a 1974 Broadway musical by Jerry Herman that dramatizes the turbulent relationship between silent film director Mack Sennett and his star Mabel Normand.
  • B. Crazy for You
    Crazy for You is a Tony Award–winning Broadway musical comedy featuring the songs of George and Ira Gershwin, known for its energetic choreography and classic showbiz storyline.
  • C. Can-Can
    Can-Can is a 1953 Broadway musical by Cole Porter, best known for its lively Parisian setting and memorable score featuring songs like "I Love Paris."
  • D. Ziegfeld Girl
    Ziegfeld Girl is a 1941 MGM musical drama film that follows the intertwined lives and romances of three women who become performers in the famed Ziegfeld Follies.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca838a424c8190b1ecac115c2927e7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60c3c5548190926e374bbe592180 completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa08c3f0081909a9aad5599f7deb2 completed April 3, 2026, 11:12 a.m.
Created at: March 30, 2026, 6:49 p.m.