Triple

T16697063
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Grey E405742 entity
Predicate hasGivenName P17 FINISHED
Object Elizabeth unclear NED1 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: [Elizabeth Grey, hasGivenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Elizabeth Grey, hasGivenName, Elizabeth]
  • A. Elizabeth
    Elizabeth is a central character in the 1931 horror film "Frankenstein," serving as Henry Frankenstein’s fiancée and a key figure whose vulnerability heightens the story’s emotional and dramatic stakes.
  • B. Elizabeth
    Elizabeth was the Duchess of York who later became Queen Elizabeth The Queen Mother, a prominent member of the British royal family in the 20th century.
  • C. Elizabeth
    Elizabeth is the given name of Elizabeth Jane Cochrane, better known as pioneering American investigative journalist Nellie Bly.
  • D. Elizabeth
    Elizabeth of Denmark was a 16th-century Danish princess who became Electress of Brandenburg through her marriage to Joachim II Hector.
  • E. Elizabeth
    Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3832e93c48190a594c498e9cc901a completed April 18, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00919d02088190acecb1a62a100255 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:19 a.m.