Triple
T19392248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seiji Togo |
E485096
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Seiji Togo |
—
|
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: Seiji Togo | Statement: [Seiji Togo, name, Seiji Togo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seiji Togo Context triple: [Seiji Togo, name, Seiji Togo]
-
A.
Seiji Togo
chosen
Seiji Togo was a prominent 20th-century Japanese painter known for his lyrical, modernist depictions of women and everyday life.
-
B.
Takao Shimizu
Takao Shimizu is a Japanese video game producer at Nintendo best known for his work on major titles in the Super Mario series.
-
C.
Takuo Miyagishima
Takuo Miyagishima was a pioneering motion picture technology engineer recognized for his significant contributions to cinema equipment and film projection systems.
-
D.
Togo Igawa
Togo Igawa is a Japanese-born British actor known for his roles in international films and television, often portraying dignified or enigmatic characters.
-
E.
Koichi Hagiuda
Koichi Hagiuda is a Japanese Liberal Democratic Party politician who has served in senior government roles, including as Minister of Education, Culture, Sports, Science and Technology.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b45caec81909dafdf66b361effd |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.