Triple

T18824954
Position Surface form Disambiguated ID Type / Status
Subject Mine All Mine E460359 entity
Predicate hasCastMember P2308 FINISHED
Object Sam Beazley
Sam Beazley was a British actor and antiques dealer known for his character roles on stage and screen, including appearances in film, television, and theatre over several decades.
 E1344695 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: Sam Beazley | Statement: [Mine All Mine, hasCastMember, Sam Beazley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sam Beazley
Context triple: [Mine All Mine, hasCastMember, Sam Beazley]
  • A. Charles Bebb
    Charles Bebb was a prominent early 20th-century American architect based in Seattle, known for helping shape the city's skyline through major commercial and landmark buildings.
  • B. Don Bexley
    Don Bexley was an American actor and comedian best known for his role as Bubba Bexley on the television series "Sanford and Son."
  • C. Ray Peacock
    Ray Peacock is the former stage name of British comedian, writer, and podcaster Ian Boldsworth.
  • D. John Lyons
    John Lyons is a film producer best known for his work on major Hollywood comedies, including the Austin Powers series.
  • E. John Lyons
    John Lyons was a prominent British linguist and semanticist known for his influential work on theoretical linguistics and the philosophy of language.
  • 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: Sam Beazley
Triple: [Mine All Mine, hasCastMember, Sam Beazley]
Generated description
Sam Beazley was a British actor and antiques dealer known for his character roles on stage and screen, including appearances in film, television, and theatre over several decades.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sam Beazley
Target entity description: Sam Beazley was a British actor and antiques dealer known for his character roles on stage and screen, including appearances in film, television, and theatre over several decades.
  • A. Charles Bebb
    Charles Bebb was a prominent early 20th-century American architect based in Seattle, known for helping shape the city's skyline through major commercial and landmark buildings.
  • B. Don Bexley
    Don Bexley was an American actor and comedian best known for his role as Bubba Bexley on the television series "Sanford and Son."
  • C. Ray Peacock
    Ray Peacock is the former stage name of British comedian, writer, and podcaster Ian Boldsworth.
  • D. John Lyons
    John Lyons is a film producer best known for his work on major Hollywood comedies, including the Austin Powers series.
  • E. John Lyons
    John Lyons was a prominent British linguist and semanticist known for his influential work on theoretical linguistics and the philosophy of language.
  • 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_69d8dcf94c288190a06dea029ae4b223 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a6bdefac8190892d6fd5c20a431e completed April 20, 2026, 4:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a055bd068588190bc34b99796e1a3e1 completed May 14, 2026, 5:21 a.m.
NEDg Description generation batch_6a0560c0ef4c819082b51fd8cee8c738 completed May 14, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_6a05615a8a7481908ec4c6f9835ca616 completed May 14, 2026, 5:44 a.m.
Created at: April 10, 2026, 11:56 a.m.