Triple

T20393346
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Richeza of Poland E500137 entity
Predicate givenName P17 FINISHED
Object Elizabeth
Elizabeth was the given name of Elizabeth Richeza of Poland, a medieval Polish princess and queen consort in Central Europe.
E1428418 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: [Elizabeth Richeza of Poland, givenName, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Context triple: [Elizabeth Richeza of Poland, givenName, Elizabeth]
  • A. Elizabeth
    Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
  • B. Elizabeth
    Elizabeth is the middle name of Tipper Gore, the American social issues advocate and former Second Lady of the United States.
  • 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 the birth name of American actress Beanie Feldstein, known for her roles in films like "Booksmart" and "Lady Bird."
  • E. Elizabeth
    Elizabeth is a fictional character in John Steinbeck’s novel "To a God Unknown," playing a key role in the protagonist’s family and the story’s exploration of faith, land, and sacrifice.
  • 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: [Elizabeth Richeza of Poland, givenName, Elizabeth]
Generated description
Elizabeth was the given name of Elizabeth Richeza of Poland, a medieval Polish princess and queen consort in Central Europe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elizabeth
Target entity description: Elizabeth was the given name of Elizabeth Richeza of Poland, a medieval Polish princess and queen consort in Central Europe.
  • A. Elizabeth
    Elizabeth was a medieval noblewoman who held the title of Duchess of Bavaria and was known as Elizabeth of Hungary.
  • B. Elizabeth
    Elizabeth was the birth name of Princess Elizabeth of England, who later became Queen Elizabeth I, the influential Tudor monarch of England.
  • C. Elizabeth
    Elizabeth is the given name of Princess Elizabeth of Yugoslavia, a Yugoslav royal and public figure.
  • D. Elizabeth
    Elizabeth was a medieval English noblewoman, the daughter of John of Gaunt and granddaughter of King Edward III.
  • E. Elizabeth
    Elizabeth is the given name of Princess Bibesco, a Romanian-British writer and socialite active in the early 20th century.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6791144788190a0ab42cf0141b6a3 completed April 20, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0876260e548190b0ca1cdee28fe72d completed May 16, 2026, 1:50 p.m.
NEDg Description generation batch_6a0877d6b364819080b5e701acea02aa completed May 16, 2026, 1:57 p.m.
NED2 Entity disambiguation (via description) batch_6a08787cfe6c8190881554ead3cfd248 completed May 16, 2026, 2 p.m.
Created at: April 16, 2026, 11:28 a.m.