Triple

T11235507
Position Surface form Disambiguated ID Type / Status
Subject Sharon Tate E265930 entity
Predicate portrayedBy P1507 FINISHED
Object Margot Robbie E124288 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: Margot Robbie | Statement: [Sharon Tate, portrayedBy, Margot Robbie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margot Robbie
Context triple: [Sharon Tate, portrayedBy, Margot Robbie]
  • A. Margot Robbie chosen
    Margot Robbie is an Australian actress and producer known for her versatile performances in films such as "The Wolf of Wall Street," "I, Tonya," and "Barbie."
  • B. Ruby Rose
    Ruby Rose is an Australian model, DJ, and actress known for her androgynous style and roles in action films and television series such as "Orange Is the New Black."
  • C. Dakota Johnson
    Dakota Johnson is an American actress best known for starring as Anastasia Steele in the film adaptation of the erotic romance novel "Fifty Shades of Grey" and its sequels.
  • D. Elizabeth Debicki
    Elizabeth Debicki is an Australian actress known for her striking performances in films and series such as "The Great Gatsby," "The Night Manager," and "The Crown."
  • E. Ana de Armas
    Ana de Armas is a Cuban-Spanish actress known for her breakout roles in films such as "Blade Runner 2049," "Knives Out," and "Blonde."
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e904cf888190826fc964f76b5cb2 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad56013481909f931505824e3b42 completed April 19, 2026, 10:24 a.m.
Created at: April 8, 2026, 9:30 p.m.