Triple

T341896
Position Surface form Disambiguated ID Type / Status
Subject Meryl Streep E6853 entity
Predicate notableWork P4 FINISHED
Object Sophie's Choice
Sophie's Choice is a 1982 drama film, based on William Styron's novel, that follows a Holocaust survivor's harrowing past and present in postwar Brooklyn.
 E43645 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: Sophie's Choice | Statement: [Meryl Streep, notableWork, Sophie's Choice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sophie's Choice
Context triple: [Meryl Streep, notableWork, Sophie's Choice]
  • A. The Green Mile
    The Green Mile is a serialized novel by Stephen King that blends supernatural elements with a poignant death-row drama set in a 1930s Southern prison.
  • B. Sula
    Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
  • C. The Wife
    "The Wife" is a sentimental short story by Washington Irving that explores themes of love, loyalty, and devotion within marriage.
  • D. Shirley
    Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
  • E. Shirley
    Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
  • 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: Sophie's Choice
Triple: [Meryl Streep, notableWork, Sophie's Choice]
Generated description
Sophie's Choice is a 1982 drama film, based on William Styron's novel, that follows a Holocaust survivor's harrowing past and present in postwar Brooklyn.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sophie's Choice
Target entity description: Sophie's Choice is a 1982 drama film, based on William Styron's novel, that follows a Holocaust survivor's harrowing past and present in postwar Brooklyn.
  • A. The Green Mile
    The Green Mile is a serialized novel by Stephen King that blends supernatural elements with a poignant death-row drama set in a 1930s Southern prison.
  • B. Sula
    Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
  • C. The Wife
    "The Wife" is a sentimental short story by Washington Irving that explores themes of love, loyalty, and devotion within marriage.
  • D. Shirley
    Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
  • E. Shirley
    Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eafef8c88190a5932eb2c6ac4a5d completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d4e883ac81909f2acb66b7bfa540 completed March 1, 2026, 5:55 a.m.
NEDg Description generation batch_69a3d56bead08190aefe0a5c6fef843e completed March 1, 2026, 5:58 a.m.
NED2 Entity disambiguation (via description) batch_69a3d62b40148190819686eda8669d6d completed March 1, 2026, 6:01 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.