Triple

T12600287
Position Surface form Disambiguated ID Type / Status
Subject Bergisches Land E300838 entity
Predicate contains P35 FINISHED
Object Much E915219 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: Much | Statement: [Bergisches Land, contains, Much]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Much
Context triple: [Bergisches Land, contains, Much]
  • A. Much
    Much is a Canadian specialty television channel best known for its music-related programming and pop culture content, formerly branded as MuchMusic.
  • B. Much chosen
    Much is a municipality in the Rhein-Sieg district of North Rhine-Westphalia, Germany, known for its rural character and scenic landscapes in the Bergisches Land region.
  • C. Most
    Most is an industrial city in the Ústí nad Labem Region of the Czech Republic, historically known for coal mining and extensive postwar urban redevelopment.
  • D. Big Amount
    Big Amount is a trap-influenced hip-hop track by 2 Chainz featuring Drake, known for its catchy hook and luxurious, boastful lyrics.
  • E. a lot
    "a lot" is a Grammy-nominated hip-hop song by 21 Savage featuring J. Cole, known for its introspective lyrics and social commentary.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954d1f6ac8190ab21ca7bcbc80129 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ec92c6c8190bd2d193e70940407 completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:09 p.m.