Triple

T3970918
Position Surface form Disambiguated ID Type / Status
Subject Applause E92332 entity
Predicate screenwriter P2831 FINISHED
Object Beth Brown
Beth Brown is a screenwriter known for her work on the film "Applause."
E443618 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: Beth Brown | Statement: [Applause, screenwriter, Beth Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beth Brown
Context triple: [Applause, screenwriter, Beth Brown]
  • A. Rachel Brown
    Rachel Brown is a central fictional character in the play "Inherit the Wind," portrayed as a conflicted young schoolteacher torn between her religious upbringing and her sympathy for the accused teacher in the evolution trial.
  • B. Pamela Brown
    Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
  • C. Gail Brown
    Gail Brown is an American actress and the sister of acclaimed film and television actress Karen Black.
  • D. Lorraine Baines
    Lorraine Baines is a central character in the "Back to the Future" film series, best known as Marty McFly’s mother whose teenage life in 1955 becomes the focus of his time-traveling adventures.
  • E. Laura Brown
    Laura Brown is a central character in Michael Cunningham’s novel and its film adaptation "The Hours," depicted as a 1950s housewife struggling with depression and the constraints of domestic life.
  • 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: Beth Brown
Triple: [Applause, screenwriter, Beth Brown]
Generated description
Beth Brown is a screenwriter known for her work on the film "Applause."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Beth Brown
Target entity description: Beth Brown is a screenwriter known for her work on the film "Applause."
  • A. Rachel Brown
    Rachel Brown is a central fictional character in the play "Inherit the Wind," portrayed as a conflicted young schoolteacher torn between her religious upbringing and her sympathy for the accused teacher in the evolution trial.
  • B. Pamela Brown
    Pamela Brown was a British stage and film actress known for her intense character roles in mid-20th-century cinema and theatre.
  • C. Gail Brown
    Gail Brown is an American actress and the sister of acclaimed film and television actress Karen Black.
  • D. Lorraine Baines
    Lorraine Baines is a central character in the "Back to the Future" film series, best known as Marty McFly’s mother whose teenage life in 1955 becomes the focus of his time-traveling adventures.
  • E. Laura Brown
    Laura Brown is a central character in Michael Cunningham’s novel and its film adaptation "The Hours," depicted as a 1950s housewife struggling with depression and the constraints of domestic life.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef995d27881908b24a5b2ef57455f completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6371762c08190ab0b829777e62540 completed March 15, 2026, 4:35 a.m.
NEDg Description generation batch_69b639659cb88190b1023e00d24d964a completed March 15, 2026, 4:45 a.m.
NED2 Entity disambiguation (via description) batch_69b63a020cc48190a28e6bd0b3a7c5c1 completed March 15, 2026, 4:48 a.m.
Created at: March 9, 2026, 3:32 p.m.