Triple

T3474891
Position Surface form Disambiguated ID Type / Status
Subject Machete Kills E73347 entity
Predicate stars P1956 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: [Machete Kills, stars, Michelle Rodriguez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michelle Rodriguez
Context triple: [Machete Kills, stars, 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. 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."
  • E. Eva Mendes
    Eva Mendes is an American actress and model known for her roles in films such as "Training Day," "Hitch," and "The Place Beyond the Pines."
  • 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_69ad85b2fed48190948c8765e453d270 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb580d4c819080bcc0bccd1e18e2 completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69b432f3af6c8190ba09e3ab8fbad7da completed March 13, 2026, 3:53 p.m.
Created at: March 8, 2026, 3:17 p.m.