Triple

T4484863
Position Surface form Disambiguated ID Type / Status
Subject Star Trek: Discovery E107210 entity
Predicate composer P1361 FINISHED
Object Jeff Russo E418030 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: Jeff Russo | Statement: [Star Trek: Discovery, composer, Jeff Russo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Russo
Context triple: [Star Trek: Discovery, composer, Jeff Russo]
  • A. Jeff Russo chosen
    Jeff Russo is an American composer and musician best known for his atmospheric scores for film, television, and video games, including series like Fargo and Star Trek: Discovery.
  • B. Max Zaritsky
    Max Zaritsky was an American labor leader and union organizer who played a key role in the early development of industrial unionism in the United States.
  • C. Andrew Solt
    Andrew Solt was a Hungarian-American screenwriter and producer best known for his work on mid-20th-century films and later for creating music-related documentaries and television programs.
  • D. Jeff Groth
    Jeff Groth is a film editor best known for his work on the critically acclaimed 2019 psychological thriller "Joker."
  • 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.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52a758f48190b6b59ca0d9207c2a completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd56ada9508190ab5566490c527d3f completed March 20, 2026, 2:16 p.m.
Created at: March 20, 2026, 12:59 p.m.