Triple

T15121712
Position Surface form Disambiguated ID Type / Status
Subject Beauty and a Beat E361186 entity
Predicate writer P1360 FINISHED
Object Max Martin E185694 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: Max Martin | Statement: [Beauty and a Beat, writer, Max Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Martin
Context triple: [Beauty and a Beat, writer, Max Martin]
  • A. Max Martin chosen
    Max Martin is a Swedish songwriter and record producer renowned for crafting numerous global pop hits for artists like Britney Spears, Backstreet Boys, Taylor Swift, and Katy Perry.
  • B. Greg Kurstin
    Greg Kurstin is a Grammy-winning American producer, songwriter, and multi-instrumentalist known for his work with major artists across pop and rock music.
  • C. RedOne
    RedOne is a Moroccan-Swedish record producer and songwriter known for crafting global pop and dance hits for artists like Lady Gaga, Jennifer Lopez, and Nicki Minaj.
  • D. Dr. Luke
    Dr. Luke is an American pop music producer and songwriter known for crafting numerous chart-topping hits for major artists in the 2000s and 2010s.
  • E. Bill Danoff
    Bill Danoff is an American songwriter and singer best known for co-writing hits like "Take Me Home, Country Roads" and "Afternoon Delight."
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0059f69a881909929a037a0eef702 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7f4abd08190b47c9daff2921919 completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 3:06 a.m.