Triple

T14703271
Position Surface form Disambiguated ID Type / Status
Subject Ralph Breaks the Internet E345360 entity
Predicate voiceCastMember P9616 FINISHED
Object Gal Gadot E199710 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: Gal Gadot | Statement: [Ralph Breaks the Internet, voiceCastMember, Gal Gadot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gal Gadot
Context triple: [Ralph Breaks the Internet, voiceCastMember, Gal Gadot]
  • A. Gal Gadot chosen
    Gal Gadot is an Israeli actress and model best known internationally for portraying Wonder Woman in the DC Extended Universe films.
  • 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. 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."
  • D. Margot Robbie
    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."
  • E. Scarlett Johansson
    Scarlett Johansson is an American actress known for her versatile film roles, including major parts in the Marvel Cinematic Universe and acclaimed performances in both independent and blockbuster movies.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6071e5c8190bb5509c859135c2d completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0861c308190af0b5da403ecb321 completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:28 a.m.