Triple

T15732159
Position Surface form Disambiguated ID Type / Status
Subject The Afterparty E381370 entity
Predicate composer P1361 FINISHED
Object Daniel Pemberton E79203 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: Daniel Pemberton | Statement: [The Afterparty, composer, Daniel Pemberton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Pemberton
Context triple: [The Afterparty, composer, Daniel Pemberton]
  • A. Daniel Pemberton chosen
    Daniel Pemberton is a British composer known for his innovative and eclectic film scores across major Hollywood and independent productions.
  • B. Lorne Balfe
    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.
  • C. Ron Goodwin
    Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
  • D. Michael Abels
    Michael Abels is an American composer best known for his innovative, genre-blending film scores for Jordan Peele’s movies, including Get Out, Us, and Nope.
  • E. Grant Kirkhope
    Grant Kirkhope is a British composer and musician best known for creating iconic soundtracks for classic video games such as Banjo-Kazooie, GoldenEye 007, and the Donkey Kong series.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd3614481908b2694b1d3550058 completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82fed7888190b45f28ac91e0079e completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:46 a.m.