Triple

T3858906
Position Surface form Disambiguated ID Type / Status
Subject Just Go with It E90086 entity
Predicate starredActor P5563 FINISHED
Object Brooklyn Decker E388172 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: Brooklyn Decker | Statement: [Just Go with It, starredActor, Brooklyn Decker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brooklyn Decker
Context triple: [Just Go with It, starredActor, Brooklyn Decker]
  • A. Brooklyn Decker chosen
    Brooklyn Decker is an American model and actress known for her Sports Illustrated Swimsuit Issue appearances and roles in films and television comedies.
  • B. Abby Dahlkemper
    Abby Dahlkemper is an American professional soccer defender and World Cup champion who has played prominently in the National Women's Soccer League and for the United States women's national team.
  • C. Shauneen Bruder
    Shauneen Bruder is a Canadian business leader and executive who has served as chancellor of the University of Guelph.
  • D. Crystal Dunn
    Crystal Dunn is an American professional soccer player and World Cup champion known for her versatility and impact for club and country.
  • E. Holly Bankemper
    Holly Bankemper is an American attorney best known as the wife of former NFL wide receiver and sportscaster Cris Collinsworth.
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec1e68f88190941c39221486f6ae completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b504228220819082e11b316ba79b08 completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:19 p.m.