Triple

T14657216
Position Surface form Disambiguated ID Type / Status
Subject Dopesick E344141 entity
Predicate composer P1361 FINISHED
Object Lorne Balfe E13895 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: Lorne Balfe | Statement: [Dopesick, composer, Lorne Balfe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lorne Balfe
Context triple: [Dopesick, composer, Lorne Balfe]
  • A. Lorne Balfe chosen
    Lorne Balfe is a Scottish composer and producer known for his work on major film, television, and video game scores, often in the action and blockbuster genres.
  • B. Dario Marianelli
    Dario Marianelli is an Italian film composer known for his evocative scores for movies such as Atonement, Pride & Prejudice, and Darkest Hour.
  • C. Daniel Pemberton
    Daniel Pemberton is a British composer known for his innovative and eclectic film scores across major Hollywood and independent productions.
  • D. Geoffrey Faithfull
    Geoffrey Faithfull was a British cinematographer known for his work on numerous films from the silent era through the mid-20th century, including the classic science fiction horror film "Village of the Damned."
  • E. Richard Shepherd
    Richard Shepherd was an American film producer best known for his work on classic movies such as "Breakfast at Tiffany's."
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb51a562c819098971447db4b29f7 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5de0b98819094c32765e4cb3f9c completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:27 a.m.