Triple

T614650
Position Surface form Disambiguated ID Type / Status
Subject Ramin Djawadi E12176 entity
Predicate name P16 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: [Ramin Djawadi, name, Ramin Djawadi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ramin Djawadi
Context triple: [Ramin Djawadi, name, 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. 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.
  • C. 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.
  • D. 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."
  • E. Thomas Newman
    Thomas Newman is an acclaimed American film composer known for his distinctive, atmospheric scores for movies such as "American Beauty," "The Shawshank Redemption," and "Skyfall."
  • 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_69a493309df48190a327f748e88049a6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49e0a0f588190b953fdb585263307 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc8ff78c8190954d33f9e4556cca completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:35 p.m.