Triple

T9821119
Position Surface form Disambiguated ID Type / Status
Subject Broderick Crawford E238532 entity
Predicate spouse P13 FINISHED
Object Kay Griffith
Kay Griffith was an American film actress active in the 1930s and 1940s, known for her supporting roles in Hollywood productions.
 E826403 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: Kay Griffith | Statement: [Broderick Crawford, spouse, Kay Griffith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kay Griffith
Context triple: [Broderick Crawford, spouse, Kay Griffith]
  • A. Amy Eshleman
    Amy Eshleman is an American former public librarian and education advocate best known as the wife of former Chicago mayor Lori Lightfoot.
  • B. Karen Barad
    Karen Barad is a feminist theorist and physicist best known for developing the concept of "agential realism," which bridges quantum physics, philosophy, and gender studies.
  • C. Michelle Mylett
    Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
  • D. Kate Sacker
    Kate Sacker is a sharp, ambitious Assistant U.S. Attorney in the television drama "Billions," known for her legal acumen and political savvy.
  • E. Kate Burroughs
    Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
  • 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: Kay Griffith
Triple: [Broderick Crawford, spouse, Kay Griffith]
Generated description
Kay Griffith was an American film actress active in the 1930s and 1940s, known for her supporting roles in Hollywood productions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kay Griffith
Target entity description: Kay Griffith was an American film actress active in the 1930s and 1940s, known for her supporting roles in Hollywood productions.
  • A. Amy Eshleman
    Amy Eshleman is an American former public librarian and education advocate best known as the wife of former Chicago mayor Lori Lightfoot.
  • B. Karen Barad
    Karen Barad is a feminist theorist and physicist best known for developing the concept of "agential realism," which bridges quantum physics, philosophy, and gender studies.
  • C. Michelle Mylett
    Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
  • D. Kate Sacker
    Kate Sacker is a sharp, ambitious Assistant U.S. Attorney in the television drama "Billions," known for her legal acumen and political savvy.
  • E. Kate Burroughs
    Kate Burroughs is the central protagonist of the film "The Four Seasons," around whom the story’s relationships and events revolve.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3147ecc81908cfca84c05a367d9 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e41e1b8081908ef5bb31c27c5264 completed April 5, 2026, 4:25 a.m.
NEDg Description generation batch_69d1e5d0da7081908e14fe4bc6623ea5 completed April 5, 2026, 4:32 a.m.
NED2 Entity disambiguation (via description) batch_69d1e6af89f88190abe63f8172182f58 completed April 5, 2026, 4:35 a.m.
Created at: March 30, 2026, 8:31 p.m.