Triple

T3241422
Position Surface form Disambiguated ID Type / Status
Subject Mickey Mouse E67971 entity
Predicate setting P1957 FINISHED
Object Mouseton E175538 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: Mouseton | Statement: [Mickey Mouse, setting, Mouseton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mouseton
Context triple: [Mickey Mouse, setting, Mouseton]
  • A. Mouseton chosen
    Mouseton is the fictional town that serves as the primary home and community setting for Mickey Mouse and many of his friends in Disney stories.
  • B. Moston
    Moston is a residential district in north Manchester, England, known for its mix of traditional terraced housing, local parks, and community amenities.
  • C. Mottingham
    Mottingham is a suburban district in southeast London, England, known for its residential character and green spaces.
  • D. Holytown
    Holytown is a small village in North Lanarkshire, Scotland, situated near Motherwell and known primarily as a residential commuter community.
  • E. Homersfield
    Homersfield is a small village and civil parish on the River Waveney in eastern England, known for its historic bridge and rural Suffolk setting.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef76d908190815bb456e366ee0a completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b27754492c819099bab9a2a3344561 completed March 12, 2026, 8:20 a.m.
Created at: March 8, 2026, 3:08 p.m.