Triple

T14172447
Position Surface form Disambiguated ID Type / Status
Subject Atonement E351242 entity
Predicate composer P1361 FINISHED
Object Ramin Djawadi E2250 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: Ramin Djawadi | Statement: [Atonement, composer, Ramin Djawadi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ramin Djawadi
Context triple: [Atonement, composer, Ramin Djawadi]
  • A. Ramin Djawadi chosen
    Ramin Djawadi is a German-Iranian composer best known for his powerful, cinematic scores for film and television, including Game of Thrones, Westworld, and major blockbuster movies.
  • B. Mychael Danna
    Mychael Danna is a Canadian film composer renowned for his evocative, often world-music-infused scores, including his Academy Award–winning work on "Life of Pi."
  • C. Clint Mansell
    Clint Mansell is a British composer best known for his atmospheric and often haunting film scores, including work on movies like Requiem for a Dream, The Fountain, and Black Swan.
  • D. James Newton Howard
    James Newton Howard is an acclaimed American composer best known for his prolific film and television scores across a wide range of genres.
  • E. Rupert Gregson-Williams
    Rupert Gregson-Williams is a British film and television composer known for scoring major Hollywood productions such as "Wonder Woman," "Aquaman," and "The Crown."
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b5dcbc8190b0cfcce5e6c6d582 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8aa0e98c81908f6b55a04cd72871 completed May 8, 2026, 7:02 a.m.
Created at: April 10, 2026, 1:01 a.m.