Triple

T10544708
Position Surface form Disambiguated ID Type / Status
Subject Michelle Rodriguez E248787 entity
Predicate name P16 FINISHED
Object Michelle Rodriguez E248787 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: Michelle Rodriguez | Statement: [Michelle Rodriguez, name, Michelle Rodriguez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michelle Rodriguez
Context triple: [Michelle Rodriguez, name, Michelle Rodriguez]
  • A. Michelle Rodriguez chosen
    Michelle Rodriguez is an American actress best known for her tough, action-oriented roles, particularly as Letty Ortiz in the Fast & Furious film franchise.
  • B. Eiza González
    Eiza González is a Mexican actress and singer known for her roles in films such as "Baby Driver," "Alita: Battle Angel," and "Welcome to Marwen," as well as the TV series "From Dusk Till Dawn: The Series."
  • C. Jordana Brewster
    Jordana Brewster is a Panamanian-American actress best known for her role as Mia Toretto in the Fast & Furious film franchise.
  • D. Angelica Bullock
    Angelica Bullock is the eccentric, status-conscious matriarch of the wealthy Bullock family in the classic screwball comedy film "My Man Godfrey."
  • E. Sanaa Lathan
    Sanaa Lathan is an American actress known for her work in film, television, and voice acting, including prominent roles in movies like "Love & Basketball" and "Brown Sugar."
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d519128cac819086c93f3bab854ac2 completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9343c5c308190952596e5254b6a65 completed April 10, 2026, 5:32 p.m.
Created at: April 6, 2026, 12:33 p.m.