Triple

T19128095
Position Surface form Disambiguated ID Type / Status
Subject How to Make an American Quilt E468238 entity
Predicate character P662 FINISHED
Object Anna
Anna is a fictional character from the novel and film "How to Make an American Quilt," one of the women whose life stories are woven into the narrative of a quilting circle.
E1360533 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: Anna | Statement: [How to Make an American Quilt, character, Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anna
Context triple: [How to Make an American Quilt, character, Anna]
  • A. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • B. Anna
    Anna is a key female resistance fighter in the World War II adventure film "The Guns of Navarone," whose complex loyalties and actions significantly impact the mission’s outcome.
  • C. Anna
    Anna is a small city in north-central Texas that forms part of the fast-growing suburban region north of Dallas.
  • D. Anna
    Anna is a biblical figure in the Book of Tobit, known as Tobit's wife and the mother of Tobias.
  • E. Anna
    Anna is the given first name of the American actress, comedian, and director Nancy Walker.
  • 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: Anna
Triple: [How to Make an American Quilt, character, Anna]
Generated description
Anna is a fictional character from the novel and film "How to Make an American Quilt," one of the women whose life stories are woven into the narrative of a quilting circle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Anna
Target entity description: Anna is a fictional character from the novel and film "How to Make an American Quilt," one of the women whose life stories are woven into the narrative of a quilting circle.
  • A. Anna
    Anna is the central protagonist of Arnold Bennett’s novel "Anna of the Five Towns," a young woman navigating love, duty, and religious constraint in an industrial English setting.
  • B. Anna
    Anna is a central fictional character in Michael Ondaatje's novel "Divisadero," around whom much of the story's emotional and narrative complexity revolves.
  • C. Anna
    Anna is a supporting character in the biographical film "Can You Ever Forgive Me?", involved in the world of literary forgery surrounding the protagonist.
  • D. Anna
    Anna is a fictional character played by British actress Naomi Ackie, known for her work in film and television.
  • E. Anna
    Anna is the given first name of the fictional character Nana Coupeau from Émile Zola’s novel "Nana."
  • 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_69d8dd0796a48190b34ce4cd9d3f3be5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3ceb5808190b3b53d9e8df3605a completed April 20, 2026, 8:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a06f247fca48190b2edf75e1d3cc317 completed May 15, 2026, 10:15 a.m.
NEDg Description generation batch_6a06f34a4f1c8190b08e2ecddcdf2c27 completed May 15, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_6a06f3d5b3408190b5fe843039dd8a74 completed May 15, 2026, 10:22 a.m.
Created at: April 10, 2026, 12:05 p.m.