Triple

T6437520
Position Surface form Disambiguated ID Type / Status
Subject Melissa Fumero E129935 entity
Predicate name P16 FINISHED
Object Melissa Fumero E129935 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: Melissa Fumero | Statement: [Melissa Fumero, name, Melissa Fumero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melissa Fumero
Context triple: [Melissa Fumero, name, Melissa Fumero]
  • A. Melissa Fumero chosen
    Melissa Fumero is an American actress best known for playing Detective Amy Santiago on the television comedy series "Brooklyn Nine-Nine."
  • B. Aurora Bernárdez
    Aurora Bernárdez was an Argentine literary translator and critic best known for her long partnership and collaboration with writer Julio Cortázar.
  • C. Caity Lotz
    Caity Lotz is an American actress, dancer, and director best known for her role as Sara Lance/White Canary in the Arrowverse television series, particularly DC's Legends of Tomorrow.
  • D. Karen Olivo
    Karen Olivo is a Tony Award–winning American stage actress and singer known for her acclaimed performances in major Broadway productions such as In the Heights, West Side Story, and Moulin Rouge! The Musical.
  • E. Molly Gordon
    Molly Gordon is an American actress and director known for her roles in films like "Booksmart" and "Good Boys" and the TV series "The Bear."
  • 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_69c0084caac48190a7bc2ad8ba44536f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c06964186c8190aeeb0038f4696032 completed March 22, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640f2915c8190aea3578dcd77dd5f completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:45 p.m.