Triple

T984757
Position Surface form Disambiguated ID Type / Status
Subject Star Trek (2009 film) E21253 entity
Predicate cinematographyBy P1953 FINISHED
Object Dan Mindel E51081 NE FINISHED

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: Dan Mindel | Statement: [Star Trek (2009 film), cinematographyBy, Dan Mindel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Mindel
Context triple: [Star Trek (2009 film), cinematographyBy, Dan Mindel]
  • A. Dan Mindel chosen
    Dan Mindel is a British cinematographer known for his work on major blockbuster films, including entries in the Star Trek and Star Wars franchises.
  • B. Michael Markowitz
    Michael Markowitz is an American comedy writer best known for co-writing the hit film "Horrible Bosses."
  • C. Rich Kleiman
    Rich Kleiman is an American sports agent and entrepreneur best known as Kevin Durant’s longtime business partner and co-founder of the sports and entertainment company Boardroom and the investment firm Thirty Five Ventures.
  • D. Matt Weitzman
    Matt Weitzman is an American television writer and producer best known as a co-creator and executive producer of the animated series "American Dad!"
  • E. Nat Mauldin
    Nat Mauldin is an American screenwriter and television writer known for his work on family-oriented films and popular TV comedies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4959fe48190a78bd811cbc888ab completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae5150360881909dabd3d6d12f83e1 completed March 9, 2026, 4:49 a.m.
Created at: March 1, 2026, 7:41 p.m.