Triple

T6222444
Position Surface form Disambiguated ID Type / Status
Subject Dexter E139146 entity
Predicate composer P1361 FINISHED
Object Daniel Licht
Daniel Licht was an American composer best known for his dark, atmospheric scores for film and television, particularly the acclaimed crime drama series "Dexter."
E577742 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: Daniel Licht | Statement: [Dexter, composer, Daniel Licht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Licht
Context triple: [Dexter, composer, Daniel Licht]
  • A. Michael Seitzman
    Michael Seitzman is an American screenwriter and producer known for his work on films such as "North Country" and for creating and producing several television series.
  • B. Michael Klein
    Michael Klein is the father of Canadian author and activist Naomi Klein.
  • C. Michael Gelman
    Michael Gelman is a longtime American television producer best known for his work shaping and overseeing the daytime talk show "Live!" through its various host pairings.
  • D. 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.
  • E. David Rosenbloom
    David Rosenbloom is a film editor known for his work on major Hollywood productions, including the science fiction movie "Transcendence."
  • 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: Daniel Licht
Triple: [Dexter, composer, Daniel Licht]
Generated description
Daniel Licht was an American composer best known for his dark, atmospheric scores for film and television, particularly the acclaimed crime drama series "Dexter."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Daniel Licht
Target entity description: Daniel Licht was an American composer best known for his dark, atmospheric scores for film and television, particularly the acclaimed crime drama series "Dexter."
  • A. Michael Seitzman
    Michael Seitzman is an American screenwriter and producer known for his work on films such as "North Country" and for creating and producing several television series.
  • B. Michael Klein
    Michael Klein is the father of Canadian author and activist Naomi Klein.
  • C. Michael Gelman
    Michael Gelman is a longtime American television producer best known for his work shaping and overseeing the daytime talk show "Live!" through its various host pairings.
  • D. 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.
  • E. David Rosenbloom
    David Rosenbloom is a film editor known for his work on major Hollywood productions, including the science fiction movie "Transcendence."
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bddb688190add53172a7445d01 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20dcc5e788190a510cac6bbad4830 completed March 24, 2026, 4:06 a.m.
NEDg Description generation batch_69c21498cfc0819097d1fa9cb10f7a92 completed March 24, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c215689f288190a54fb3fc7984455a completed March 24, 2026, 4:39 a.m.
Created at: March 22, 2026, 4:22 p.m.