Triple

T13517557
Position Surface form Disambiguated ID Type / Status
Subject Shekhar Kapur E322804 entity
Predicate directed P7373 FINISHED
Object Elizabeth
"Elizabeth" is a 1998 historical drama film chronicling the early reign of Queen Elizabeth I of England.
 E64313 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: [Shekhar Kapur, directed, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Context triple: [Shekhar Kapur, directed, Elizabeth]
  • A. Elizabeth
    Elizabeth is a key character in Nathaniel Hawthorne’s short story “The Minister’s Black Veil,” serving as Reverend Hooper’s fiancée whose reaction to his mysterious veil highlights themes of isolation and the fear of hidden sin.
  • B. Elizabeth
    Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
  • C. Elizabeth
    Elizabeth is the central character in the Broadway musical "If/Then," a woman who explores how a single choice can lead to radically different life paths.
  • D. Elizabeth
    Elizabeth is the given name of Jane Elizabeth Ebsworth Oriel, the late wife of British broadcaster and naturalist David Attenborough.
  • E. Elizabeth
    Elizabeth is the given name of Elizabeth Jane Cochrane, better known as pioneering American investigative journalist Nellie Bly.
  • 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: [Shekhar Kapur, directed, Elizabeth]
Generated description
"Elizabeth" is a 1998 historical drama film chronicling the early reign of Queen Elizabeth I of England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Target entity description: "Elizabeth" is a 1998 historical drama film chronicling the early reign of Queen Elizabeth I of England.
  • A. Elizabeth chosen
    "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.
  • B. Elizabeth
    Elizabeth is the first name of acclaimed New Zealand filmmaker Jane Campion, known for directing films such as "The Piano."
  • C. Elizabeth
    Elizabeth is the birth name of American actress Téa Leoni, known for her roles in film and television such as "Madam Secretary."
  • D. Elizabeth
    "Elizabeth" is a biographical work by J. Randy Taraborrelli that chronicles the life and career of actress Elizabeth Taylor.
  • E. Elizabeth
    Elizabeth is the intelligent, witty, and strong-minded heroine of Jane Austen’s novel "Pride and Prejudice."
  • F. None of above.

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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa27f048190bed33a98e28c8d09 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76ba344e0819098da09416a913851 completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77640b5308190aaa50e8d5d871832 completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f778f01700819099c3e9cbc84f29e4 completed May 3, 2026, 4:33 p.m.
Created at: April 9, 2026, 9:44 p.m.