Triple

T16585170
Position Surface form Disambiguated ID Type / Status
Subject James Frain E402937 entity
Predicate notableWork P4 FINISHED
Object Elizabeth
"Elizabeth" is a 1998 historical drama film about the early reign of Queen Elizabeth I of England, acclaimed for its performances and direction.
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: [James Frain, notableWork, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [James Frain, notableWork, Elizabeth]
  • A. Elizabeth
    Elizabeth is the middle name of Diane Elizabeth Dern, an individual likely known in relation to the Dern family.
  • B. Elizabeth
    Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
  • C. Elizabeth
    Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
  • D. Elizabeth
    Elizabeth is the middle name of Tipper Gore, the American social issues advocate and former Second Lady of the United States.
  • E. Elizabeth
    Elizabeth was the birth name of Princess Elizabeth of England, who later became Queen Elizabeth I, the influential Tudor monarch of England.
  • 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: [James Frain, notableWork, Elizabeth]
Generated description
"Elizabeth" is a 1998 historical drama film about the early reign of Queen Elizabeth I of England, acclaimed for its performances and direction.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Target entity description: "Elizabeth" is a 1998 historical drama film about the early reign of Queen Elizabeth I of England, acclaimed for its performances and direction.
  • 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 was the birth name of Princess Elizabeth of England, who later became Queen Elizabeth I, the influential Tudor monarch of England.
  • D. Elizabeth
    "Elizabeth" is a French film featuring actress Fanny Ardant in a prominent role.
  • E. Elizabeth
    Elizabeth is a supporting character in the crime drama film "Hustlers," which follows a group of strippers who scheme to swindle wealthy Wall Street clients.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3599b057881909fcb8bbb156633a8 completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee8812c81908ef74636bf39d44a completed May 10, 2026, 11:41 a.m.
NEDg Description generation batch_6a0070024cb4819092ee0ce1320f0905 completed May 10, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a00707959a081909fc04947624abbe5 completed May 10, 2026, 11:48 a.m.
Created at: April 10, 2026, 5:16 a.m.