Triple

T20388540
Position Surface form Disambiguated ID Type / Status
Subject Thinner E498022 entity
Predicate musicBy P1952 FINISHED
Object Daniel Licht NE NERFINISHED

How this triple was built (2 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: [Thinner, musicBy, Daniel Licht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Licht
Context triple: [Thinner, musicBy, Daniel Licht]
  • A. Daniel Licht chosen
    Daniel Licht was an American composer best known for his dark, atmospheric scores for film and television, particularly the acclaimed crime drama series "Dexter."
  • B. 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.
  • C. Jeremy Leven
    Jeremy Leven is an American screenwriter, director, and novelist known for adapting romantic and character-driven stories for film, including the hit movie "The Notebook."
  • D. Jeffrey Blitz
    Jeffrey Blitz is an American film and television director and producer known for his work on projects like the documentary "Spellbound," the comedy "Rocket Science," and episodes of "The Office."
  • E. Michael Yarmush
    Michael Yarmush is a Canadian-American actor best known as the original voice of the title character in the animated children's television series "Arthur."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790d9e5881908bde7da9e5e541a0 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.