Triple

T5140760
Position Surface form Disambiguated ID Type / Status
Subject I Got Rhythm E115944 entity
Predicate originalPerformer P11499 FINISHED
Object Ethel Merman E129340 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: Ethel Merman | Statement: [I Got Rhythm, originalPerformer, Ethel Merman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ethel Merman
Context triple: [I Got Rhythm, originalPerformer, Ethel Merman]
  • A. Ethel Merman chosen
    Ethel Merman was a powerhouse American stage and film actress and singer, famed for her brassy voice and iconic performances in classic Broadway musicals such as "Gypsy" and "Annie Get Your Gun."
  • B. Gwen Verdon
    Gwen Verdon was an acclaimed American actress and dancer best known for her Tony Award–winning performances in Broadway musicals such as "Damn Yankees" and "Chicago."
  • C. Helen Merrill
    Helen Merrill is an American jazz vocalist renowned for her cool, introspective style and influential recordings with leading jazz musicians of the 1950s.
  • D. Gloria DeHaven
    Gloria DeHaven was an American actress and singer best known for her roles in classic Hollywood musicals of the 1940s and 1950s.
  • E. Betty Garrett
    Betty Garrett was an American actress, comedian, singer, and dancer known for her energetic performances in mid-20th-century Hollywood musicals and later in popular television sitcoms.
  • 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_69bd44459a988190a772a5c2ec6a1965 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd787e5fe88190834042a73d4d9619 completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06a74d4c8190a353007c564ba2f6 completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:43 p.m.