Triple
T4083246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiroyuki Sanada |
E87526
|
entity |
| Predicate | notableRole |
P22
|
FINISHED |
| Object |
Toru in Bullet Train (2022 film)
Toru in Bullet Train (2022 film) is a key character portrayed by Hiroyuki Sanada, serving as a seasoned, vengeful crime boss whose actions drive much of the film’s central conflict.
|
E411599
|
NE FINISHED |
How this triple was built (4 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: Toru in Bullet Train (2022 film) | Statement: [Hiroyuki Sanada, notableRole, Toru in Bullet Train (2022 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toru in Bullet Train (2022 film) Context triple: [Hiroyuki Sanada, notableRole, Toru in Bullet Train (2022 film)]
-
A.
Shinya
Shinya is a Japanese given name commonly used for males.
-
B.
Ronin
Ronin is a 1998 action thriller film directed by John Frankenheimer, best known for its intricate espionage plot and realistic, high-intensity car chases set in France.
-
C.
Shoto
Shoto is an upscale residential neighborhood in Tokyo’s Shibuya ward, known for its quiet streets, cultural institutions, and affluent atmosphere.
-
D.
Ninja
Ninja is a fast, small, and focused build system designed to efficiently handle incremental builds in large software projects.
-
E.
Shiki, Saitama
Shiki, Saitama is a city in Saitama Prefecture, Japan, known as a residential suburb within the Greater Tokyo metropolitan area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Toru in Bullet Train (2022 film) Triple: [Hiroyuki Sanada, notableRole, Toru in Bullet Train (2022 film)]
Generated description
Toru in Bullet Train (2022 film) is a key character portrayed by Hiroyuki Sanada, serving as a seasoned, vengeful crime boss whose actions drive much of the film’s central conflict.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Toru in Bullet Train (2022 film) Target entity description: Toru in Bullet Train (2022 film) is a key character portrayed by Hiroyuki Sanada, serving as a seasoned, vengeful crime boss whose actions drive much of the film’s central conflict.
-
A.
Shinya
Shinya is a Japanese given name commonly used for males.
-
B.
Ronin
Ronin is a 1998 action thriller film directed by John Frankenheimer, best known for its intricate espionage plot and realistic, high-intensity car chases set in France.
-
C.
Shoto
Shoto is an upscale residential neighborhood in Tokyo’s Shibuya ward, known for its quiet streets, cultural institutions, and affluent atmosphere.
-
D.
Ninja
Ninja is a fast, small, and focused build system designed to efficiently handle incremental builds in large software projects.
-
E.
Shiki, Saitama
Shiki, Saitama is a city in Saitama Prefecture, Japan, known as a residential suburb within the Greater Tokyo metropolitan area.
- F. None of above. chosen
Provenance (5 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc7933b481909bb3e02c6c04c8ee |
completed | March 9, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b562c6456081908cca823ebb13936a |
completed | March 14, 2026, 1:29 p.m. |
| NEDg | Description generation | batch_69b563b5cc108190bb9684abafa608af |
completed | March 14, 2026, 1:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5646606f08190930451ac372154cd |
completed | March 14, 2026, 1:36 p.m. |
Created at: March 9, 2026, 3:39 p.m.