Triple

T14363125
Position Surface form Disambiguated ID Type / Status
Subject The Campaign E356153 entity
Predicate starring P1507 FINISHED
Object Katherine LaNasa E362415 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: Katherine LaNasa | Statement: [The Campaign, starring, Katherine LaNasa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katherine LaNasa
Context triple: [The Campaign, starring, Katherine LaNasa]
  • A. Katherine LaNasa chosen
    Katherine LaNasa is an American actress, former ballet dancer, and choreographer known for her work in film and television, including roles in series like "Three Sisters" and "Deception."
  • B. Nicole Lambert
    Nicole Lambert is a film producer known for her work on the crime drama prequel "The Many Saints of Newark."
  • C. Lindsay Merrill
    Lindsay Merrill is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Merrill.
  • D. Lana Morris
    Lana Morris was a British film and television actress known for her work in mid-20th-century comedies and dramas.
  • E. Natalie Baszile
    Natalie Baszile is an American author best known for her novel "Queen Sugar," which was adapted into the acclaimed television series created by Ava DuVernay and produced by Oprah Winfrey.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fabec088190bd8128371b29e958 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a023005e760819081b723a7246c78ce completed May 11, 2026, 7:37 p.m.
Created at: April 10, 2026, 1:15 a.m.