Triple

T22977276
Position Surface form Disambiguated ID Type / Status
Subject Allison Becker E571359 entity
Predicate portrayedBy P1507 FINISHED
Object Laura Benanti 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: Laura Benanti | Statement: [Allison Becker, portrayedBy, Laura Benanti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura Benanti
Context triple: [Allison Becker, portrayedBy, Laura Benanti]
  • A. Laura Benanti chosen
    Laura Benanti is a Tony Award–winning American actress and singer known for her acclaimed performances in numerous Broadway musicals and television series.
  • B. Beth Leavel
    Beth Leavel is a Tony Award–winning American stage actress and singer best known for her work in numerous Broadway musicals.
  • C. Rachel Messerer
    Rachel Messerer was a member of the prominent Messerer family of Russian ballet, known as a relative of legendary ballerina Maya Plisetskaya.
  • D. Eileen Brennan
    Eileen Brennan was an American actress known for her sharp comic timing and memorable character roles in films like "Private Benjamin" and "Clue," as well as numerous television appearances.
  • E. Kimberly Elise
    Kimberly Elise is an American actress known for her powerful performances in films such as "Set It Off," "Beloved," and "Diary of a Mad Black Woman."
  • 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_69e245b3c50481908bb3741ec9f40862 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18292f3788190ab4e9d559e0070c8 completed April 29, 2026, 4:01 a.m.
Created at: April 17, 2026, 3:48 p.m.