Triple

T6792954
Position Surface form Disambiguated ID Type / Status
Subject Mary, Queen of Hungary E155980 entity
Predicate givenName P17 FINISHED
Object Mary
Mary was a 16th-century Habsburg archduchess who became Queen consort of Hungary and Bohemia through her marriage to King Louis II.
E620439 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: Mary | Statement: [Mary, Queen of Hungary, givenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary, Queen of Hungary, givenName, Mary]
  • A. Mary
    Mary is a fictional character in B.F. Skinner’s utopian novel "Walden Two," representing one of the community’s young members shaped by its behaviorist social principles.
  • B. Mary
    Mary is the birth name of American actress, singer, and dancer Debbie Reynolds, a major Hollywood star of the mid-20th century.
  • C. Mary
    Mary is the middle name of Katherine Mary Dewar, a component of her full personal name.
  • D. Mary
    Mary is the given name of Mary J. Blige, the acclaimed American singer, songwriter, and actress often called the "Queen of Hip-Hop Soul."
  • E. Mary
    Mary is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's kind and well-behaved cousin.
  • 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: Mary
Triple: [Mary, Queen of Hungary, givenName, Mary]
Generated description
Mary was a 16th-century Habsburg archduchess who became Queen consort of Hungary and Bohemia through her marriage to King Louis II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary was a 16th-century Habsburg archduchess who became Queen consort of Hungary and Bohemia through her marriage to King Louis II.
  • A. Mary
    Mary, Princess Royal and Princess of Orange, was the eldest daughter of King Charles I of England and the wife of William II of Orange, making her a key figure in 17th-century Anglo-Dutch royal relations.
  • B. Mary
    Mary I of England was the 16th-century Queen of England and Ireland best known for her attempt to restore Roman Catholicism and for the Marian persecutions that earned her the nickname "Bloody Mary."
  • C. Mary
    Mary II of England was a late 17th-century Queen of England, Scotland, and Ireland who ruled jointly with her husband William III after the Glorious Revolution.
  • D. Mary
    Mary of Waltham, Duchess of Brittany, was a 14th-century English princess and daughter of King Edward III who became duchess through her marriage to John IV, Duke of Brittany.
  • E. Mary
    Mary, Duchess of Gloucester and Edinburgh, was a British princess and the wife of Prince William Frederick, a grandson of King George II.
  • 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_69c6881844448190a65822d9b39d7f88 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2af6f908190809e39b73894e513 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a76f0c8819097e19e016988f0b4 completed March 28, 2026, 12:01 a.m.
NEDg Description generation batch_69c71d2b9f748190bfa4438b47aef820 completed March 28, 2026, 12:13 a.m.
NED2 Entity disambiguation (via description) batch_69c71da5ef54819099250aca55b1b27f completed March 28, 2026, 12:15 a.m.
Created at: March 27, 2026, 2:15 p.m.