Triple

T17545951
Position Surface form Disambiguated ID Type / Status
Subject Experimental Jet Set, Trash and No Star E427323 entity
Predicate labelImprint P2763 FINISHED
Object DGC 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: DGC | Statement: [Experimental Jet Set, Trash and No Star, labelImprint, DGC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DGC
Context triple: [Experimental Jet Set, Trash and No Star, labelImprint, DGC]
  • A. DGC
    DGC is the United Nations Department of Global Communications, responsible for promoting global awareness and understanding of the UN’s work through strategic communication and public outreach.
  • B. DGC chosen
    DGC is a record label imprint best known for signing influential alternative rock and grunge artists in the late 1980s and 1990s.
  • C. DGP
    DGP is the highest-ranking police officer in an Indian state or union territory, responsible for overseeing the entire state police force.
  • D. DGF
    DGF is the vehicle registration code used for the Dingolfing-Landau district in Bavaria, Germany.
  • E. DCG
    DCG is the Dental College of Georgia, a dental school that provides education, research, and clinical services in dentistry.
  • 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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45461643881909b106bafb89253b3 completed April 19, 2026, 4:04 a.m.
Created at: April 10, 2026, 5:49 a.m.