Triple

T3357793
Position Surface form Disambiguated ID Type / Status
Subject Mary Tyler Moore E70646 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 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 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
    Mary is the given first name of the acclaimed American actress Meryl Streep.
  • 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 birth name of the acclaimed British actress Vivien Leigh, renowned for her roles in "Gone with the Wind" and "A Streetcar Named Desire."
  • 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 Cassatt, the renowned American Impressionist painter known for her depictions of women and children.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb244435c81908e35d2aa36ec4f46 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bbbc3a48190bc17572ba3136948 completed March 12, 2026, 11:26 p.m.
NEDg Description generation batch_69b34e45a6c08190a0011eaa60f3d50a completed March 12, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69b34eba517881908806b1ac285448ff completed March 12, 2026, 11:39 p.m.
Created at: March 8, 2026, 3:13 p.m.