Triple

T14290007
Position Surface form Disambiguated ID Type / Status
Subject Mary Tyler Moore E354283 entity
Predicate givenName P17 FINISHED
Object Mary
Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
E354283 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 Tyler Moore, givenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary Tyler Moore, givenName, 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 Tyler Moore, givenName, Mary]
Generated description
Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
  • A. Mary chosen
    Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
  • B. Mary
    Mary is the given name of American character actress Marjorie Main, known for her roles in classic Hollywood films.
  • C. Mary
    Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
  • D. Mary
    Mary is the given first name of the acclaimed American actress Meryl Streep.
  • E. Mary
    Mary is the given name of American actress, singer, director, and screenwriter Mary Kay Place, known for her work in film and television since the 1970s.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6981e9148190baf2ed56a7b7340e completed April 14, 2026, 4:21 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, 1:11 a.m.