Triple

T17445409
Position Surface form Disambiguated ID Type / Status
Subject Ben Diskin E424768 entity
Predicate notableWork P4 FINISHED
Object Digimon Fusion 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: Digimon Fusion | Statement: [Ben Diskin, notableWork, Digimon Fusion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Digimon Fusion
Context triple: [Ben Diskin, notableWork, Digimon Fusion]
  • A. Digimon chosen
    Digimon is a Japanese media franchise centered on digital monsters that spans anime, video games, toys, and other merchandise.
  • B. Augmon
    Augmon is the surname of former American professional basketball player Stacey Augmon, known for his defensive prowess in the NBA.
  • C. Bakugan Dragonoid
    Bakugan Dragonoid is a Monster Jam monster truck themed after the Bakugan franchise’s dragon-like Dragonoid character, known for its striking design and high-flying freestyle performances.
  • D. Doryumu
    Doryumu is a town in Ghana located near the Shai Hills Resource Reserve in the Greater Accra Region.
  • E. Dangan Ressha
    Dangan Ressha is the Japanese nickname meaning "Bullet Train," famously used for the pioneering 0 Series Shinkansen high-speed trains.
  • 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44ffafec48190b25980318cea353f completed April 19, 2026, 3:46 a.m.
Created at: April 10, 2026, 5:47 a.m.