Triple

T6100664
Position Surface form Disambiguated ID Type / Status
Subject Out West with the Hardys E135984 entity
Predicate castMember P1668 FINISHED
Object John Dilson
John Dilson was an American character actor active in the 1930s and 1940s, known for his numerous supporting roles in Hollywood films.
E591679 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: John Dilson | Statement: [Out West with the Hardys, castMember, John Dilson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Dilson
Context triple: [Out West with the Hardys, castMember, John Dilson]
  • A. John Dolman
    John Dolman was an English clergyman and benefactor of the late 16th century best known for establishing Pocklington School in Yorkshire.
  • B. Arthur Dignam
    Arthur Dignam was an Australian actor known for his distinctive character roles in film, television, and theatre.
  • C. Richard Bristow
    Richard Bristow was a 16th-century English Catholic scholar and theologian who contributed to the development and annotation of the Douay–Rheims Bible.
  • D. John Glynn
    John Glynn was an 18th-century English lawyer and politician whose prominence led to Glynn County in Georgia being named in his honor.
  • E. David Semple
    David Semple was a British bacteriologist best known for developing an early anti-rabies vaccine while serving in the Indian Medical Service.
  • 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: John Dilson
Triple: [Out West with the Hardys, castMember, John Dilson]
Generated description
John Dilson was an American character actor active in the 1930s and 1940s, known for his numerous supporting roles in Hollywood films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John Dilson
Target entity description: John Dilson was an American character actor active in the 1930s and 1940s, known for his numerous supporting roles in Hollywood films.
  • A. John Dolman
    John Dolman was an English clergyman and benefactor of the late 16th century best known for establishing Pocklington School in Yorkshire.
  • B. Arthur Dignam
    Arthur Dignam was an Australian actor known for his distinctive character roles in film, television, and theatre.
  • C. Richard Bristow
    Richard Bristow was a 16th-century English Catholic scholar and theologian who contributed to the development and annotation of the Douay–Rheims Bible.
  • D. John Glynn
    John Glynn was an 18th-century English lawyer and politician whose prominence led to Glynn County in Georgia being named in his honor.
  • E. David Semple
    David Semple was a British bacteriologist best known for developing an early anti-rabies vaccine while serving in the Indian Medical Service.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b3aa9908190865be98ada141d37 completed March 22, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6409d48408190b2048c07272277ac completed March 27, 2026, 8:32 a.m.
NEDg Description generation batch_69c6421cfa948190b62735451ede82f0 completed March 27, 2026, 8:38 a.m.
NED2 Entity disambiguation (via description) batch_69c6426f194c819086fa4baffe8d237b completed March 27, 2026, 8:40 a.m.
Created at: March 22, 2026, 4:13 p.m.