Triple

T21090389
Position Surface form Disambiguated ID Type / Status
Subject Mie Hama E519621 entity
Predicate employer P7 FINISHED
Object Toho Studios 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: Toho Studios | Statement: [Mie Hama, employer, Toho Studios]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toho Studios
Context triple: [Mie Hama, employer, Toho Studios]
  • A. Toho chosen
    Toho is a major Japanese film production and distribution company best known worldwide for creating and owning the Godzilla franchise.
  • B. Tōei
    Tōei is a small rural town in eastern Aichi Prefecture, Japan, known for its mountainous terrain and traditional hot spring and forestry industries.
  • C. Toei
    Toei is the public transportation operator run by the Tokyo Metropolitan Government, managing subway lines, buses, and other transit services in Tokyo.
  • D. Daiei Film
    Daiei Film was a major Japanese film studio best known for producing classic kaiju and genre films, including the Gamera series.
  • E. Shochiku
    Shochiku is a major Japanese film and theater production and distribution company, historically known for its influential role in the development of Japanese cinema.
  • 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7094ea7f881909db83bf6961b41ec completed April 21, 2026, 5:21 a.m.
Created at: April 16, 2026, 2:50 p.m.