Triple

T8452914
Position Surface form Disambiguated ID Type / Status
Subject Blue Collar E199843 entity
Predicate hasTrack P3284 FINISHED
Object Fever unclear NED1 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: Fever | Statement: [Blue Collar, hasTrack, Fever]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fever
Context triple: [Blue Collar, hasTrack, Fever]
  • A. Fever
    "Fever" is a 2018 Afrobeats single by Nigerian artist Wizkid, known for its sultry vibe and viral music video featuring Tiwa Savage.
  • B. Fever
    "Fever" is a classic, sultry jazz-pop song popularized by Peggy Lee, renowned for its minimalist arrangement and intimate vocal style.
  • C. Fever
    "Fever" is a track by the experimental hip-hop group Black Milk, known for its intricate production and innovative approach to rap music.
  • D. Chills and Fever
    "Chills and Fever" is a collection of poems by American poet and critic John Crowe Ransom, showcasing his formal precision, irony, and themes of Southern life and modern dislocation.
  • E. Fever 103°
    Fever 103° is a confessional poem by Sylvia Plath that vividly explores themes of illness, purification, and transcendence through intense, hallucinatory imagery.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe48aee388190864ef1186d5ee419 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1dda289c81908e0cc8e1a504caa1 completed April 2, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:09 p.m.