Triple

T13599817
Position Surface form Disambiguated ID Type / Status
Subject Natalia Kills E324914 entity
Predicate recordLabel P1500 FINISHED
Object KonLive Distribution E200827 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: KonLive Distribution | Statement: [Natalia Kills, recordLabel, KonLive Distribution]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KonLive Distribution
Context triple: [Natalia Kills, recordLabel, KonLive Distribution]
  • A. KonLive Distribution chosen
    KonLive Distribution is a record label and music imprint founded by Akon, known for launching and distributing the early releases of major pop acts such as Lady Gaga.
  • B. Onda Entertainment
    Onda Entertainment is a film and television production company known for working on projects such as the crime thriller "Savages" (2012).
  • C. Clarius Entertainment
    Clarius Entertainment is an American film distribution company known for releasing independent and mid-budget feature films.
  • D. Nettwerk
    Nettwerk is a Canadian independent record label and management company known for working with a diverse roster of alternative, electronic, and world music artists.
  • E. StoneBrook Entertainment
    StoneBrook Entertainment is a film production company known for producing the romantic comedy feature "She Wants Me."
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0795acc8190a08667ab9dcb0d44 completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bcc1ed88190bbf6c83001703b84 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.