Triple

T3053591
Position Surface form Disambiguated ID Type / Status
Subject Eric Cantona E60426 entity
Predicate appearedIn P795 FINISHED
Object Elizabeth E64313 NE FINISHED

How this triple was built (2 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: [Eric Cantona, appearedIn, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Eric Cantona, appearedIn, Elizabeth]
  • A. Elizabeth
    Elizabeth is the formal first name of Bess Truman, who served as First Lady of the United States as the wife of President Harry S. Truman.
  • B. 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.
  • C. 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.
  • D. Elizabeth
    Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
  • E. Elizabeth
    Elizabeth is the given name of Princess Alexandra, The Honourable Lady Ogilvy, a member of the British royal family and cousin of Queen Elizabeth II.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9bf51b5081908ce355a76cfa9e3c completed March 8, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f8724bd481909ea8c71e92801096 completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:01 p.m.