Triple

T10201708
Position Surface form Disambiguated ID Type / Status
Subject Almost Human E238897 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: [Almost Human, composer, Lorne Balfe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lorne Balfe
Context triple: [Almost Human, 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdee40cb7481908a1bf4d5636eb8ef completed April 2, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d32afa75ec8190bbaf2e69b4ee24f1 completed April 6, 2026, 3:39 a.m.
Created at: March 30, 2026, 9:14 p.m.