Triple
T22768318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yasujirō Ozu |
E563184
|
entity |
| Predicate | notableCollaboration |
P8554
|
FINISHED |
| Object | Setsuko Hara |
—
|
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: Setsuko Hara | Statement: [Yasujirō Ozu, notableCollaboration, Setsuko Hara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Setsuko Hara Context triple: [Yasujirō Ozu, notableCollaboration, Setsuko Hara]
-
A.
Setsuko Hara
chosen
Setsuko Hara was a celebrated Japanese film actress renowned for her nuanced performances in classic works by directors such as Yasujirō Ozu and Akira Kurosawa.
-
B.
Machiko Yamada
Machiko Yamada is a prominent Japanese figure skating coach known for mentoring world champion skater Midori Ito and developing numerous elite athletes.
-
C.
Nobuko Imai
Nobuko Imai is a renowned Japanese violist celebrated for her international solo career, chamber music performances, and influential teaching.
-
D.
Nobuko Otowa
Nobuko Otowa was a prominent Japanese actress known for her frequent collaborations with director Kaneto Shindō and her acclaimed performances in postwar Japanese cinema.
-
E.
Shinsaku Ohara
Shinsaku Ohara is a film producer known for his work on the movie "The Assignment."
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a81d3348190b005a43a5e03d406 |
completed | April 29, 2026, 3:26 a.m. |
Created at: April 17, 2026, 3:27 p.m.