Triple

T17350129
Position Surface form Disambiguated ID Type / Status
Subject Every Girl Should Be Married E421785 entity
Predicate castMember P1668 FINISHED
Object Richard Gaines — NE ONDG

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: Richard Gaines | Statement: [Every Girl Should Be Married, castMember, Richard Gaines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Richard Gaines
Context triple: [Every Girl Should Be Married, castMember, Richard Gaines]
  • A. Leo Harrington
    Leo Harrington is an American logician and mathematician known for his influential work in mathematical logic, particularly in recursion theory and set theory.
  • B. Richard Wells
    Richard Wells is a British composer best known for his atmospheric scores for film and television, including the supernatural drama series "Being Human."
  • C. John Gurney
    John Gurney was a prominent English Quaker banker and member of the influential Gurney family of Norwich.
  • D. Richard Clark
    Richard Clark is a British television director known for his work on popular series including episodes of Doctor Who.
  • E. Richard Goodwin
    Richard Goodwin is a British film producer best known for his work on acclaimed literary adaptations and period dramas, including the 1984 film "A Passage to India."
  • 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: Richard Gaines
Triple: [Every Girl Should Be Married, castMember, Richard Gaines]
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Richard Gaines
Target entity description: Richard Gaines was an American character actor known for his supporting roles in numerous Hollywood films of the 1940s and 1950s.
  • A. Leo Harrington
    Leo Harrington is an American logician and mathematician known for his influential work in mathematical logic, particularly in recursion theory and set theory.
  • B. Richard Wells
    Richard Wells is a British composer best known for his atmospheric scores for film and television, including the supernatural drama series "Being Human."
  • C. John Gurney
    John Gurney was a prominent English Quaker banker and member of the influential Gurney family of Norwich.
  • D. Richard Clark
    Richard Clark is a British television director known for his work on popular series including episodes of Doctor Who.
  • E. Richard Goodwin
    Richard Goodwin is a British film producer best known for his work on acclaimed literary adaptations and period dramas, including the 1984 film "A Passage to India."
  • F. None of above. chosen

Provenance (4 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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a2bd0a881909e71c89773d9273c completed April 19, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0195585e5881909b0ad386b65112ba completed May 11, 2026, 8:37 a.m.
NEDg Description generation batch_6a0195c365348190bc5ae9d39094e6f3 in_progress May 11, 2026, 8:39 a.m.
Created at: April 10, 2026, 5:44 a.m.