Triple

T12526653
Position Surface form Disambiguated ID Type / Status
Subject Princess Elizabeth of Yugoslavia E299456 entity
Predicate givenName P17 FINISHED
Object Elizabeth
Elizabeth is the given name of Princess Elizabeth of Yugoslavia, a Yugoslav royal and public figure.
E988265 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: [Princess Elizabeth of Yugoslavia, givenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Princess Elizabeth of Yugoslavia, givenName, 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
    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 protagonist of the interactive narrative game "If/Then," around whom the story’s key choices and emotional developments revolve.
  • D. 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.
  • 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: [Princess Elizabeth of Yugoslavia, givenName, Elizabeth]
Generated description
Elizabeth is the given name of Princess Elizabeth of Yugoslavia, a Yugoslav royal and public figure.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Target entity description: Elizabeth is the given name of Princess Elizabeth of Yugoslavia, a Yugoslav royal and public figure.
  • A. Elizabeth
    Elizabeth is the middle name of Princess Beatrice of York, a member of the British royal family.
  • B. Elizabeth
    Elizabeth is the given name of Lady Elizabeth Spencer-Churchill, a member of the prominent Spencer-Churchill aristocratic family in Britain.
  • C. 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.
  • D. Elizabeth
    Elizabeth was a Greek and Danish princess of the early 20th century, born into the royal families of both Greece and Denmark.
  • E. Elizabeth
    Elizabeth is the given name of Elizabeth Camilla Julia "Lisl" Godowsky, an individual associated with the Godowsky family.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545d7e6c819080c3a85c18caa1ae completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bc393808190add527030a928517 completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64c535c9881908e5bf07d13fa73c5 completed May 2, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_69f6508afef08190ac7a19b1ee90141e completed May 2, 2026, 7:29 p.m.
Created at: April 8, 2026, 9:57 p.m.