Triple

T14312931
Position Surface form Disambiguated ID Type / Status
Subject Mary Howland E354877 entity
Predicate hasGivenName P17 FINISHED
Object Mary
Mary is a common female given name with biblical origins, widely used in many cultures and languages.
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 Howland, hasGivenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary Howland, hasGivenName, Mary]
  • A. Mary
    Mary is the given name of the American suspense novelist Mary Higgins Clark, known for her bestselling mystery and thriller books.
  • B. Mary
    Mary is the given name of Mary Catherine Bateson, an American cultural anthropologist and writer known for her work on learning and the human life cycle.
  • C. Mary
    Mary of Lancaster was a 14th-century English noblewoman, daughter of Henry, 3rd Earl of Lancaster, and a member of the influential House of Lancaster.
  • D. Mary
    Mary is the middle name of Joseph Plunkett, the Irish nationalist, poet, and 1916 Easter Rising leader.
  • E. Mary
    Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
  • 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 Howland, hasGivenName, Mary]
Generated description
Mary is a common female given name with biblical origins, widely used in many cultures and languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary is a common female given name with biblical origins, widely used in many cultures and languages.
  • A. Mary chosen
    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.
  • 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 name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
  • 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 the given name of Mary Sidney, an English Renaissance noblewoman, writer, and literary patron.
  • F. None of above.

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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b386d0819087d14f3ce84a1997 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d1fee448190bcafb37dd6618d60 completed May 8, 2026, 1:32 a.m.
NEDg Description generation batch_69fd3e5f333c8190bdce30a813bea59e completed May 8, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_69fd3ed1fe288190b83dc432b61f0b4f completed May 8, 2026, 1:39 a.m.
Created at: April 10, 2026, 1:12 a.m.