Triple

T19646162
Position Surface form Disambiguated ID Type / Status
Subject Celebrations for a Grey Day E471675 entity
Predicate hasTrack P3284 FINISHED
Object Downtown 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: Downtown | Statement: [Celebrations for a Grey Day, hasTrack, Downtown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Downtown
Context triple: [Celebrations for a Grey Day, hasTrack, Downtown]
  • A. Downtown
    Downtown is an American television series featuring Mariska Hargitay in a leading role.
  • B. Downtown
    Downtown is the central business and commercial district of Washington, D.C., known for its offices, shops, restaurants, and proximity to major landmarks.
  • C. Downtown chosen
    "Downtown" is a funk- and hip hop-influenced single by Macklemore & Ryan Lewis, known for its nostalgic homage to old-school rap and mopeds.
  • D. Downtown
    Downtown refers to the central urban area of a city, typically its main commercial and business district.
  • E. Downtown
    "Downtown" is a 2010 country-pop song by Lady A (formerly Lady Antebellum), known for its upbeat tempo and playful lyrics about escaping routine for a night out in the city.
  • 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e641250e108190a707452fefc87041 completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:44 p.m.