Triple

T6292138
Position Surface form Disambiguated ID Type / Status
Subject Future E141041 entity
Predicate mixtape P24091 FINISHED
Object Monster E82632 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: Monster | Statement: [Future, mixtape, Monster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monster
Context triple: [Future, mixtape, Monster]
  • A. Monster
    Monster is a 2003 biographical crime drama film in which Charlize Theron delivers an Oscar-winning performance as serial killer Aileen Wuornos.
  • B. Monster
    Monster is a town in the Dutch province of South Holland, known for its coastal location near the North Sea and its greenhouse horticulture.
  • C. Monster chosen
    "Monster" is a standout track from Kanye West’s critically acclaimed album *My Beautiful Dark Twisted Fantasy*, known for its high-profile guest verses and dark, aggressive themes.
  • D. Monster
    Monster is a popular energy drink brand known for its high-caffeine beverages and aggressive, extreme-sports-oriented marketing.
  • E. Monsters
    Monsters is a professional ice hockey team based in Cleveland, Ohio, competing in the American Hockey League as the affiliate of the NHL’s Columbus Blue Jackets.
  • 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_69c008cdf2ac8190bb640c94478fb4ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0641ea224819097b6962e6014c690 completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c51983afd081908d2cfeaeccb40bcb completed March 26, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:27 p.m.