Triple

T10365334
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Bennet E244236 entity
Predicate givenName P17 FINISHED
Object Elizabeth
Elizabeth is the intelligent, witty, and strong-minded heroine of Jane Austen’s novel "Pride and Prejudice."
E861445 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: Elizabeth | Statement: [Elizabeth Bennet, givenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Elizabeth Bennet, givenName, Elizabeth]
  • A. Elizabeth
    Elizabeth "Betty" Ford was the influential First Lady of the United States from 1974 to 1977, renowned for her advocacy on women's rights, breast cancer awareness, and addiction treatment.
  • B. Elizabeth
    Elizabeth is the middle name of Diane Elizabeth Dern, an individual likely known in relation to the Dern family.
  • C. Elizabeth
    Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
  • D. Elizabeth
    Elizabeth is an alternate given name associated with Mary Surratt, the American boardinghouse owner convicted and executed for her role in the conspiracy to assassinate President Abraham Lincoln.
  • E. Elizabeth
    Elizabeth is the birth name of American actress and comedian Ellie Kemper, known for her roles in "The Office" and "Unbreakable Kimmy Schmidt."
  • 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: Elizabeth
Triple: [Elizabeth Bennet, givenName, Elizabeth]
Generated description
Elizabeth is the intelligent, witty, and strong-minded heroine of Jane Austen’s novel "Pride and Prejudice."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Target entity description: Elizabeth is the intelligent, witty, and strong-minded heroine of Jane Austen’s novel "Pride and Prejudice."
  • A. Elizabeth
    Elizabeth, often called Beth March, is the gentle, musically gifted younger sister in Louisa May Alcott’s novel "Little Women."
  • B. Elizabeth
    Elizabeth is the central protagonist of the interactive narrative game "If/Then," around whom the story’s key choices and emotional developments revolve.
  • C. Elizabeth
    Elizabeth is a central character in Helen Garner's novella "The Children’s Bach," around whom much of the story’s domestic and emotional tension revolves.
  • D. Elizabeth
    Elizabeth is a comedic, high-strung fiancée character in the 1974 Mel Brooks film "Young Frankenstein," known for her dramatic personality and memorable scenes.
  • E. Elizabeth
    "Elizabeth" is a 1998 historical drama film that chronicles the early reign of Queen Elizabeth I of England, starring Cate Blanchett in the title role.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e96f25f48190a41c8b0206b9238c completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fb827cd4819094bead4304795c33 completed April 9, 2026, 7:18 p.m.
NEDg Description generation batch_69d822d303888190aa556287b3b1cc03 completed April 9, 2026, 10:06 p.m.
NED2 Entity disambiguation (via description) batch_69d859b05a3881908c97cb173d160e44 completed April 10, 2026, 2 a.m.
Created at: April 6, 2026, noon