Triple

T13057396
Position Surface form Disambiguated ID Type / Status
Subject DJ Got Us Fallin' in Love E327612 entity
Predicate songwriter P1141 FINISHED
Object Savan Kotecha E653108 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: Savan Kotecha | Statement: [DJ Got Us Fallin' in Love, songwriter, Savan Kotecha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Savan Kotecha
Context triple: [DJ Got Us Fallin' in Love, songwriter, Savan Kotecha]
  • A. Savan Kotecha chosen
    Savan Kotecha is an American songwriter and record producer best known for crafting numerous global pop hits for artists like One Direction, Ariana Grande, and The Weeknd.
  • B. Divyank Turakhia
    Divyank Turakhia is an Indian serial tech entrepreneur and billionaire best known for building and selling multiple internet and ad-tech companies, including those under the Directi Group.
  • C. Karan Patel
    Karan Patel is an Indian television actor best known for his role as Raman Bhalla in the popular Hindi TV series "Yeh Hai Mohabbatein."
  • D. Dillon Mitra
    Dillon Mitra is an actor known for his role in the culinary drama film "The Hundred-Foot Journey."
  • E. Anish Savjani
    Anish Savjani is an American film producer known for his work on acclaimed independent films, including the thriller "Green Room."
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980bd305c8190bcf191b2d35ec8de completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5ff8c308190a40274c68a1c5da3 completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 8:58 p.m.