Triple

T9854833
Position Surface form Disambiguated ID Type / Status
Subject Weeds E239556 entity
Predicate executiveProducer P7225 FINISHED
Object Matthew Salsberg
Matthew Salsberg is a television writer and producer best known for his work on the dark comedy series "Weeds."
E838766 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: Matthew Salsberg | Statement: [Weeds, executiveProducer, Matthew Salsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Salsberg
Context triple: [Weeds, executiveProducer, Matthew Salsberg]
  • A. Josh Kesselman
    Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
  • B. Adam Siegel
    Adam Siegel is a film producer known for his work on action and genre movies, including the 2008 thriller "Wanted."
  • C. Jonathan Littman
    Jonathan Littman is a television producer best known for his executive production work on the CSI franchise and other major crime and drama series.
  • D. Michael Wincott
    Michael Wincott is a Canadian character actor known for his distinctive raspy voice and memorable villainous roles in films such as The Crow, Robin Hood: Prince of Thieves, and Nope.
  • E. Michael Filerman
    Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
  • 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: Matthew Salsberg
Triple: [Weeds, executiveProducer, Matthew Salsberg]
Generated description
Matthew Salsberg is a television writer and producer best known for his work on the dark comedy series "Weeds."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew Salsberg
Target entity description: Matthew Salsberg is a television writer and producer best known for his work on the dark comedy series "Weeds."
  • A. Josh Kesselman
    Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
  • B. Adam Siegel
    Adam Siegel is a film producer known for his work on action and genre movies, including the 2008 thriller "Wanted."
  • C. Jonathan Littman
    Jonathan Littman is a television producer best known for his executive production work on the CSI franchise and other major crime and drama series.
  • D. Michael Wincott
    Michael Wincott is a Canadian character actor known for his distinctive raspy voice and memorable villainous roles in films such as The Crow, Robin Hood: Prince of Thieves, and Nope.
  • E. Michael Filerman
    Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
  • 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_69ca84e4fdc08190a624425bcef98665 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3960fb481909c90d6d6cafc6222 completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d299c51ea08190902e03552fbe7ebb completed April 5, 2026, 5:20 p.m.
NEDg Description generation batch_69d29b7430248190b8965eaf1286dd7c completed April 5, 2026, 5:27 p.m.
NED2 Entity disambiguation (via description) batch_69d29c7ba9f081908f4614098d6c954b completed April 5, 2026, 5:31 p.m.
Created at: March 30, 2026, 8:34 p.m.