Triple

T8665845
Position Surface form Disambiguated ID Type / Status
Subject Karl Malden E205671 entity
Predicate spouse P13 FINISHED
Object Mona Greenberg
Mona Greenberg was the longtime wife of acclaimed American actor Karl Malden.
E776896 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: Mona Greenberg | Statement: [Karl Malden, spouse, Mona Greenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona Greenberg
Context triple: [Karl Malden, spouse, Mona Greenberg]
  • A. Nora Grossman
    Nora Grossman is a film producer best known for her work on the acclaimed historical drama "The Imitation Game."
  • B. Arline Greenbaum
    Arline Greenbaum was the first wife of physicist Richard Feynman, remembered for their deeply devoted relationship during her struggle with tuberculosis in the 1940s.
  • C. Susanna Fogel
    Susanna Fogel is an American filmmaker and screenwriter known for directing sharp, character-driven comedies and dramedies, often centered on complex female friendships and offbeat humor.
  • D. Sally Grossman
    Sally Grossman was an American figure in the 1960s folk and rock scene, best known for appearing on the iconic cover of Bob Dylan’s album "Bringing It All Back Home."
  • E. Carol Mendelsohn
    Carol Mendelsohn is an American television producer and writer best known for her influential work shaping the CSI franchise and modern crime procedural dramas.
  • 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: Mona Greenberg
Triple: [Karl Malden, spouse, Mona Greenberg]
Generated description
Mona Greenberg was the longtime wife of acclaimed American actor Karl Malden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mona Greenberg
Target entity description: Mona Greenberg was the longtime wife of acclaimed American actor Karl Malden.
  • A. Nora Grossman
    Nora Grossman is a film producer best known for her work on the acclaimed historical drama "The Imitation Game."
  • B. Arline Greenbaum
    Arline Greenbaum was the first wife of physicist Richard Feynman, remembered for their deeply devoted relationship during her struggle with tuberculosis in the 1940s.
  • C. Susanna Fogel
    Susanna Fogel is an American filmmaker and screenwriter known for directing sharp, character-driven comedies and dramedies, often centered on complex female friendships and offbeat humor.
  • D. Sally Grossman
    Sally Grossman was an American figure in the 1960s folk and rock scene, best known for appearing on the iconic cover of Bob Dylan’s album "Bringing It All Back Home."
  • E. Carol Mendelsohn
    Carol Mendelsohn is an American television producer and writer best known for her influential work shaping the CSI franchise and modern crime procedural dramas.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48a1dd1481908c56abca48fcd562 completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d016e84df4819092b442216a5f6c9e completed April 3, 2026, 7:37 p.m.
NEDg Description generation batch_69d019059e8481909a696575366aa0b6 completed April 3, 2026, 7:46 p.m.
NED2 Entity disambiguation (via description) batch_69d019a2736c8190880c8f3786cf353b completed April 3, 2026, 7:48 p.m.
Created at: March 30, 2026, 6:31 p.m.