Triple

T15164392
Position Surface form Disambiguated ID Type / Status
Subject Brighten the Corners E362297 entity
Predicate hasPart P35 FINISHED
Object Stereo E362305 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: Stereo | Statement: [Brighten the Corners, hasPart, Stereo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stereo
Context triple: [Brighten the Corners, hasPart, Stereo]
  • A. Stereo chosen
    "Stereo" is an indie rock song by the American band Pavement, known for its offbeat lyrics and inclusion on their 1997 album "Brighten the Corners."
  • B. Moving in Stereo
    "Moving in Stereo" is a synth-driven rock song by The Cars, best known for its atmospheric production and prominent use in the film *Fast Times at Ridgemont High*.
  • C. Binaural
    Binaural is a 2000 studio album by American rock band Pearl Jam, noted for its experimental production and use of binaural recording techniques.
  • D. Mono vs Stereo
    Mono vs Stereo is an independent Christian rock record label known for releasing albums by bands such as Relient K.
  • E. Surround Sound
    "Surround Sound" is a popular hip-hop track by rapper JID, known for its intricate wordplay, dynamic flows, and hard-hitting production.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0064b21ac81908b793bdbd741bcd8 completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69febffdf65c8190bf629dfc32b97caa completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:08 a.m.