Triple

T20653423
Position Surface form Disambiguated ID Type / Status
Subject Julie Wilson E507558 entity
Predicate recordLabel P1500 FINISHED
Object DRG Records NE NERFINISHED

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: DRG Records | Statement: [Julie Wilson, recordLabel, DRG Records]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DRG Records
Context triple: [Julie Wilson, recordLabel, DRG Records]
  • A. DRG Records chosen
    DRG Records is a music label known for its catalog of cast recordings, cabaret, and vocal performances, particularly in the Broadway and theater genres.
  • B. DWA Records
    DWA Records is an Italian dance music label best known for releasing Eurodance hits in the 1990s.
  • C. Dot Records
    Dot Records was a prominent American record label, especially known for its success in the 1950s and 1960s with pop and rock artists such as Pat Boone.
  • D. Homestead Records
    Homestead Records was an influential American independent record label active in the 1980s and early 1990s, known for releasing pioneering underground rock, punk, and noise music.
  • E. Kudu Records
    Kudu Records was a jazz and soul-oriented record label, best known as a subsidiary imprint of CTI Records that focused on funk-influenced, commercially accessible jazz in the 1970s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bf58c081908e52a4500e03ff83 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b2eb8c7081908e7dd7f7fa375190 completed April 20, 2026, 11:12 p.m.
Created at: April 16, 2026, 11:43 a.m.