Triple

T23468205
Position Surface form Disambiguated ID Type / Status
Subject Eat Pray Love E569152 entity
Predicate screenwriter P2831 FINISHED
Object Jennifer Salt NE NERFINISHED

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: Jennifer Salt | Statement: [Eat Pray Love, screenwriter, Jennifer Salt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Salt
Context triple: [Eat Pray Love, screenwriter, Jennifer Salt]
  • A. Jennifer Salt chosen
    Jennifer Salt is an American actress and screenwriter known for her roles in 1970s films and television, as well as for co-writing acclaimed series such as American Horror Story and Feud.
  • B. Laura Harring
    Laura Harring is a Mexican-American actress best known for her acclaimed role in David Lynch's film "Mulholland Drive."
  • C. Wendie Malick
    Wendie Malick is an American actress best known for her roles in television series such as "Just Shoot Me!" and "Hot in Cleveland."
  • D. Jennifer Hart
    Jennifer Hart is a glamorous, intelligent, and adventurous wealthy socialite and amateur sleuth from the television series "Hart to Hart."
  • E. Jennifer Lame
    Jennifer Lame is an American film editor known for her frequent collaborations with prominent directors such as Christopher Nolan, including her work on the 2023 biographical thriller "Oppenheimer."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a6fd280c81908aae05f0851466eb completed April 29, 2026, 6:36 a.m.
Created at: April 17, 2026, 5:54 p.m.