Triple

T23373973
Position Surface form Disambiguated ID Type / Status
Subject The Sweet Sweet Fantasy Tour E593554 entity
Predicate setlistFeature P33226 FINISHED
Object Obsessed 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: Obsessed | Statement: [The Sweet Sweet Fantasy Tour, setlistFeature, Obsessed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Obsessed
Context triple: [The Sweet Sweet Fantasy Tour, setlistFeature, Obsessed]
  • A. Obsessed chosen
    "Obsessed" is a 2009 R&B/pop single by Mariah Carey, known for its confrontational lyrics and catchy hook, widely interpreted as a response to rapper Eminem.
  • B. Obsessed
    "Obsessed" is a country-pop studio album by American duo Dan + Shay, featuring romantic, harmony-rich tracks that helped solidify their mainstream success.
  • C. Obsessed
    "Obsessed" is a crime thriller novel in the Michael Bennett series by James Patterson, following the NYPD detective as he tackles a particularly personal and dangerous case.
  • D. Obsessed
    Obsessed is a work by creator Ken Seng, recognized as one of his notable contributions to his field.
  • E. Obsessed
    Obsessed is a psychological thriller film centered on a woman whose dangerous fixation threatens the life and marriage of the character played by Lisa Sheridan.
  • 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_69e25d268a50819095f2fd479da8ef3f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a3b1d24881909945936cbf00876e completed April 29, 2026, 6:22 a.m.
Created at: April 17, 2026, 5:33 p.m.