Triple
T17436516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madadayo |
E424013
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Toshie Negishi |
—
|
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: Toshie Negishi | Statement: [Madadayo, castMember, Toshie Negishi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toshie Negishi Context triple: [Madadayo, castMember, Toshie Negishi]
-
A.
Toshie Negishi
chosen
Toshie Negishi is a Japanese actress known for her work in film and television, including roles in acclaimed dramas and art-house productions.
-
B.
Toshie Kobayashi
Toshie Kobayashi is an actress known for her role in Akira Kurosawa’s film "Rhapsody in August."
-
C.
Mieko Harada
Mieko Harada is a Japanese actress best known internationally for her intense portrayal of Lady Kaede in Akira Kurosawa’s epic film "Ran."
-
D.
Atsuko Nishida
Atsuko Nishida is a Japanese illustrator and character designer best known for creating Pikachu and contributing to many iconic Pokémon designs.
-
E.
Takako Ohta
Takako Ohta is a Japanese singer and actress best known for her 1980s idol career and hit songs in the J-pop genre.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4490426008190b474ed76aca5d6f3 |
completed | April 19, 2026, 3:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.