Triple

T246659
Position Surface form Disambiguated ID Type / Status
Subject Norman Lear E5052 entity
Predicate notableWork P4 FINISHED
Object Mary Hartman, Mary Hartman
Mary Hartman, Mary Hartman is a satirical 1970s American television soap opera known for its dark humor and critique of suburban life and consumer culture.
 E31757 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 Hartman, Mary Hartman | Statement: [Norman Lear, notableWork, Mary Hartman, Mary Hartman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mary Hartman, Mary Hartman
Context triple: [Norman Lear, notableWork, Mary Hartman, Mary Hartman]
  • A. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • B. Norma
    Norma is a feminine given name used in various cultures, often considered the female counterpart of the name Norman.
  • C. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • D. Madam
    "Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
  • E. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • 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 Hartman, Mary Hartman
Triple: [Norman Lear, notableWork, Mary Hartman, Mary Hartman]
Generated description
Mary Hartman, Mary Hartman is a satirical 1970s American television soap opera known for its dark humor and critique of suburban life and consumer culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mary Hartman, Mary Hartman
Target entity description: Mary Hartman, Mary Hartman is a satirical 1970s American television soap opera known for its dark humor and critique of suburban life and consumer culture.
  • A. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • B. Norma
    Norma is a feminine given name used in various cultures, often considered the female counterpart of the name Norman.
  • C. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • D. Madam
    "Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
  • E. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25d13b8088190a3f48f0388d57496 completed Feb. 28, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a36cf64798819096218d320b00a3a9 completed Feb. 28, 2026, 10:32 p.m.
NEDg Description generation batch_69a36d713d548190afadbc7ec7509d98 completed Feb. 28, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69a36e072f188190a0961926536659c1 completed Feb. 28, 2026, 10:36 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.