Triple

T20201051
Position Surface form Disambiguated ID Type / Status
Subject Tears for Fears E493217 entity
Predicate notableWork P4 FINISHED
Object Mad World 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: Mad World | Statement: [Tears for Fears, notableWork, Mad World]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mad World
Context triple: [Tears for Fears, notableWork, Mad World]
  • A. Mad World
    "Mad World" is a popular electronic dance track by Australian DJ and producer Timmy Trumpet, known for its energetic festival sound and catchy melodic hooks.
  • B. Mad World chosen
    "Mad World" is a melancholic song originally by Tears for Fears, widely popularized by Gary Jules’ haunting cover used in the film *Donnie Darko*.
  • C. A Long and Sad Goodbye
    "A Long and Sad Goodbye" is a melancholic rock ballad by Lenny Kravitz featured on his 2008 album *It Is Time for a Love Revolution*.
  • D. Dreamland
    Dreamland is an independent film directed by Robert Schwartzman that blends offbeat romance and quirky drama.
  • E. Dreamland
    "Dreamland" is a synth-pop single by the Pet Shop Boys featuring Years & Years, known for its nostalgic yet contemporary electronic sound.
  • 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d8e0df481909c030e2a01d1862a completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:37 p.m.