Triple

T13286258
Position Surface form Disambiguated ID Type / Status
Subject Return to Me E316451 entity
Predicate mainCharacter P1183 FINISHED
Object Grace Briggs
Grace Briggs is the warm-hearted waitress and grieving widow who becomes the romantic lead opposite a heart-transplant recipient in the film "Return to Me."
E1088163 NE FINISHED

How this triple was built (4 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: Grace Briggs | Statement: [Return to Me, mainCharacter, Grace Briggs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grace Briggs
Context triple: [Return to Me, mainCharacter, Grace Briggs]
  • A. Mary Beth Johnson
    Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
  • B. Mary Beth Hughes
    Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
  • C. Erinn Bartlett
    Erinn Bartlett is an American actress and former beauty pageant titleholder known for supporting roles in film and television.
  • D. Kaye Brinker
    Kaye Brinker was the wife of American film and television actor Hugh Marlowe.
  • E. Gail Brown
    Gail Brown is an American actress and the sister of acclaimed film and television actress Karen Black.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Grace Briggs
Triple: [Return to Me, mainCharacter, Grace Briggs]
Generated description
Grace Briggs is the warm-hearted waitress and grieving widow who becomes the romantic lead opposite a heart-transplant recipient in the film "Return to Me."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Grace Briggs
Target entity description: Grace Briggs is the warm-hearted waitress and grieving widow who becomes the romantic lead opposite a heart-transplant recipient in the film "Return to Me."
  • A. Mary Beth Johnson
    Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
  • B. Mary Beth Hughes
    Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
  • C. Erinn Bartlett
    Erinn Bartlett is an American actress and former beauty pageant titleholder known for supporting roles in film and television.
  • D. Kaye Brinker
    Kaye Brinker was the wife of American film and television actor Hugh Marlowe.
  • E. Gail Brown
    Gail Brown is an American actress and the sister of acclaimed film and television actress Karen Black.
  • F. None of above. chosen

Provenance (5 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990759ebc8190a9487a59e37a69e2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd27f0e59c8190b40213e999c75feb completed May 8, 2026, 12:01 a.m.
NEDg Description generation batch_69fd2b2363f881909e04edd850166dd5 completed May 8, 2026, 12:15 a.m.
NED2 Entity disambiguation (via description) batch_69fd2cf1a1248190a97644dadf1717bc completed May 8, 2026, 12:23 a.m.
Created at: April 9, 2026, 9:27 p.m.