Triple

T14080430
Position Surface form Disambiguated ID Type / Status
Subject Lost Highway E338850 entity
Predicate producer P490 FINISHED
Object Mary Sweeney E1178691 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: Mary Sweeney | Statement: [Lost Highway, producer, Mary Sweeney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Sweeney
Context triple: [Lost Highway, producer, Mary Sweeney]
  • A. Mary Sweeney chosen
    Mary Sweeney is an American film editor, producer, and writer best known for her long-time collaboration with director David Lynch on projects such as "Lost Highway" and "Mulholland Drive."
  • B. Maureen Sweeney
    Maureen Sweeney is an Irish woman best known for her crucial World War II weather observations that influenced the timing of the D-Day landings.
  • C. Ann Sweeny
    Ann Sweeny is best known as the wife of acclaimed American television producer, director, and writer Gene Reynolds.
  • D. Sarah O’Meara
    Sarah O’Meara is known as the spouse of Australian film director Paul Cox.
  • E. Lisa McGrillis
    Lisa McGrillis is a British actress known for her work in television, film, and theatre, including roles in series like "Inspector George Gently" and "Mum."
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5f759c81909bfd60ab35b0937b completed April 14, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa11c81f481909129eef69e47d079 completed May 9, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:21 p.m.