Triple

T13695120
Position Surface form Disambiguated ID Type / Status
Subject Blunt Talk E328363 entity
Predicate character P662 FINISHED
Object Jim Stone
Jim Stone is a fictional character from the television comedy series "Blunt Talk," which stars Patrick Stewart as a British newscaster in Los Angeles.
 E1054577 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: Jim Stone | Statement: [Blunt Talk, character, Jim Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jim Stone
Context triple: [Blunt Talk, character, Jim Stone]
  • A. Mike Stone
    Mike Stone was a British record producer and audio engineer known for his work with rock and pop artists in the 1970s and 1980s.
  • B. Mike Stone
    Mike Stone is a fictional San Francisco police lieutenant and main character from the 1970s television series "The Streets of San Francisco."
  • C. John Stanier
    John Stanier is an American drummer best known for his powerful, precise playing with the alternative metal band Helmet and later with experimental rock groups like Battles.
  • D. John Stanier
    John Stanier is a cinematographer best known for his work on major action films such as "Rambo III."
  • E. Andy Stone
    Andy Stone is a central character in the British comedy series "Detectorists," known for his involvement in the world of metal detecting and the show's gentle, character-driven humor.
  • 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: Jim Stone
Triple: [Blunt Talk, character, Jim Stone]
Generated description
Jim Stone is a fictional character from the television comedy series "Blunt Talk," which stars Patrick Stewart as a British newscaster in Los Angeles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jim Stone
Target entity description: Jim Stone is a fictional character from the television comedy series "Blunt Talk," which stars Patrick Stewart as a British newscaster in Los Angeles.
  • A. Mike Stone
    Mike Stone was a British record producer and audio engineer known for his work with rock and pop artists in the 1970s and 1980s.
  • B. Mike Stone
    Mike Stone is a fictional San Francisco police lieutenant and main character from the 1970s television series "The Streets of San Francisco."
  • C. John Stanier
    John Stanier is an American drummer best known for his powerful, precise playing with the alternative metal band Helmet and later with experimental rock groups like Battles.
  • D. John Stanier
    John Stanier is a cinematographer best known for his work on major action films such as "Rambo III."
  • E. Andy Stone
    Andy Stone is a central character in the British comedy series "Detectorists," known for his involvement in the world of metal detecting and the show's gentle, character-driven humor.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8773f388190b2413b1e05fd5fd7 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f794514afc8190b334b1fc74a6cdd5 completed May 3, 2026, 6:30 p.m.
NEDg Description generation batch_69f795e361c48190b37060312e7df181 completed May 3, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_69f796e5c60c8190a19389bc4cdbd658 completed May 3, 2026, 6:41 p.m.
Created at: April 9, 2026, 9:54 p.m.