Triple

T12146817
Position Surface form Disambiguated ID Type / Status
Subject Laura Harris E289346 entity
Predicate name P16 FINISHED
Object Laura Harris E289346 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: Laura Harris | Statement: [Laura Harris, name, Laura Harris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura Harris
Context triple: [Laura Harris, name, Laura Harris]
  • A. Laura Harris chosen
    Laura Harris is a Canadian actress known for her roles in films like "The Faculty" and TV series such as "24" and "Dead Like Me."
  • B. Karen Sillas
    Karen Sillas is an American actress known for her work in independent films and television dramas, including the series "Under Suspicion."
  • C. Lori Marshall
    Lori Marshall is an American television writer and author, known for her work on sitcoms and for collaborating on books about and with her father, filmmaker Garry Marshall.
  • D. Laura Deming
    Laura Deming is a venture capitalist and longevity researcher best known for founding The Longevity Fund, which invests in companies developing therapies to extend healthy human lifespan.
  • E. Meena Harris
    Meena Harris is an American lawyer, author, and entrepreneur best known as the founder of the social justice–focused brand Phenomenal and for her activism on gender and racial equality.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915ac2ebc81909155f9b2fb4a2252 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b85782481908cca14d8e8345411 completed May 2, 2026, 7:07 p.m.
Created at: April 8, 2026, 9:49 p.m.