Triple

T16087107
Position Surface form Disambiguated ID Type / Status
Subject Daniella Pineda E390261 entity
Predicate name P16 FINISHED
Object Daniella Pineda E390261 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: Daniella Pineda | Statement: [Daniella Pineda, name, Daniella Pineda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniella Pineda
Context triple: [Daniella Pineda, name, Daniella Pineda]
  • A. Daniella Pineda chosen
    Daniella Pineda is an American actress known for her roles in film and television, including major parts in genre projects like Jurassic World: Fallen Kingdom and the live-action Cowboy Bebop series.
  • B. Daniella García
    Daniella García is a member of the García-Lorido family, known for its ties to the entertainment industry through actor Andy García and actress Dominik García-Lorido.
  • C. Daniella Alonso
    Daniella Alonso is an American actress and former fashion model known for her roles in television series such as "Revolution," "Dynasty," and various film and TV projects.
  • D. Lisa Alvarado
    Lisa Alvarado is a musician best known as a member of the experimental jazz collective Natural Information Society.
  • E. Trini Alvarado
    Trini Alvarado is an American actress known for her nuanced performances in films such as "Little Women" (1994) and "The Frighteners."
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1844f95508190a06dad0ccc9b6191 completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe48ef3608190848d4730a4361395 completed May 10, 2026, 1:51 a.m.
Created at: April 10, 2026, 4:59 a.m.