Triple

T598546
Position Surface form Disambiguated ID Type / Status
Subject Mary Anne MacLeod Trump E11441 entity
Predicate givenName P17 FINISHED
Object Mary
Mary is a feminine given name of Hebrew origin, widely used in English-speaking and many other cultures and historically associated with numerous religious and historical figures.
 E75782 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 Anne MacLeod Trump, givenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mary
Context triple: [Mary Anne MacLeod Trump, givenName, Mary]
  • A. Mary
    Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
  • B. Mary
    Mary is the given first name of Margaret Truman, the daughter of U.S. President Harry S. Truman and a noted author and singer.
  • C. 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.
  • D. Mary
    Mary, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-20th century.
  • E. Mary
    Mary is the given first name of the acclaimed American actress Meryl Streep.
  • 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 Anne MacLeod Trump, givenName, Mary]
Generated description
Mary is a feminine given name of Hebrew origin, widely used in English-speaking and many other cultures and historically associated with numerous religious and historical figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mary
Target entity description: Mary is a feminine given name of Hebrew origin, widely used in English-speaking and many other cultures and historically associated with numerous religious and historical figures.
  • A. Mary
    Mary is the given name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
  • B. Mary
    Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
  • C. Mary
    Mary is the given first name of the acclaimed American actress Meryl Streep.
  • D. Mary
    Mary is the given first name of Margaret Truman, the daughter of U.S. President Harry S. Truman and a noted author and singer.
  • E. Mary
    Mary, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d776c6c819081b41a9b55041cd5 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5238759c88190b1a960291c758447 completed March 2, 2026, 5:43 a.m.
NEDg Description generation batch_69a524233d34819092c15fdc9d6b6411 completed March 2, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69a524a0b00c8190951d1e279226ef50 completed March 2, 2026, 5:48 a.m.
Created at: March 1, 2026, 7:35 p.m.