Triple

T6501937
Position Surface form Disambiguated ID Type / Status
Subject Double Trouble E148908 entity
Predicate partOf P40 FINISHED
Object Austin music scene E15420 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: Austin music scene | Statement: [Double Trouble, partOf, Austin music scene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austin music scene
Context triple: [Double Trouble, partOf, Austin music scene]
  • A. downtown Austin
    Downtown Austin is the central business and cultural district of Austin, Texas, known for its dense skyline, live music venues, nightlife, and proximity to the Texas State Capitol and Lady Bird Lake.
  • B. Austin
    Austin is a common English surname of Anglo-Saxon origin, often associated with notable figures in philosophy, politics, and the arts.
  • C. Austin
    Austin is one of Chicago’s largest and most populous West Side community areas, known for its historic residential architecture and significant demographic and economic changes over time.
  • D. Austin
    Austin is a small historic mining town in central Nevada known for its 19th-century silver boom and remote, high-desert setting along U.S. Route 50.
  • E. Austin chosen
    Austin is a major city in central Texas known for its vibrant live music scene, tech industry, and cultural diversity.
  • 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_69c687e9ad288190bae5bcac9c8ac855 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c68ad440dc8190a074f049dbda2f55 completed March 27, 2026, 1:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb2e83cc81908f07a402e8562f1a completed March 27, 2026, 6:23 p.m.
Created at: March 27, 2026, 1:42 p.m.