Triple

T9539797
Position Surface form Disambiguated ID Type / Status
Subject My Man Godfrey E230119 entity
Predicate character P662 FINISHED
Object Angelica Bullock
Angelica Bullock is the eccentric, status-conscious matriarch of the wealthy Bullock family in the classic screwball comedy film "My Man Godfrey."
 E808426 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: Angelica Bullock | Statement: [My Man Godfrey, character, Angelica Bullock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Angelica Bullock
Context triple: [My Man Godfrey, character, Angelica Bullock]
  • A. Laila Bullock
    Laila Bullock is the adopted daughter of American actress Sandra Bullock.
  • B. Melissa Hudson
    Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
  • C. Sanaa Lathan
    Sanaa Lathan is an American actress known for her work in film, television, and voice acting, including prominent roles in movies like "Love & Basketball" and "Brown Sugar."
  • D. Lynn Collins
    Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television series.
  • E. Rebecca Washington
    Rebecca Washington is a central character on the legal drama series "The Practice," known for her work as a dedicated attorney at the show's featured law firm.
  • 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: Angelica Bullock
Triple: [My Man Godfrey, character, Angelica Bullock]
Generated description
Angelica Bullock is the eccentric, status-conscious matriarch of the wealthy Bullock family in the classic screwball comedy film "My Man Godfrey."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Angelica Bullock
Target entity description: Angelica Bullock is the eccentric, status-conscious matriarch of the wealthy Bullock family in the classic screwball comedy film "My Man Godfrey."
  • A. Laila Bullock
    Laila Bullock is the adopted daughter of American actress Sandra Bullock.
  • B. Melissa Hudson
    Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
  • C. Sanaa Lathan
    Sanaa Lathan is an American actress known for her work in film, television, and voice acting, including prominent roles in movies like "Love & Basketball" and "Brown Sugar."
  • D. Lynn Collins
    Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television series.
  • E. Rebecca Washington
    Rebecca Washington is a central character on the legal drama series "The Practice," known for her work as a dedicated attorney at the show's featured law firm.
  • 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_69ca847b1b3081908f72bc932c17cc41 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e4df6c8190a4d1160c42daa45f completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d161355e2c819099c8e6b974f97608 completed April 4, 2026, 7:06 p.m.
NEDg Description generation batch_69d16230a99481909d82d03babe6729a completed April 4, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_69d16321aba88190a7e8359dbaa5362b completed April 4, 2026, 7:14 p.m.
Created at: March 30, 2026, 8:01 p.m.