Triple
T17363807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Godzilla: Tokyo S.O.S. |
E422135
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Hiroshi Koizumi |
—
|
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: Hiroshi Koizumi | Statement: [Godzilla: Tokyo S.O.S., stars, Hiroshi Koizumi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hiroshi Koizumi Context triple: [Godzilla: Tokyo S.O.S., stars, Hiroshi Koizumi]
-
A.
Hiroshi Koizumi
chosen
Hiroshi Koizumi was a Japanese actor best known for his frequent roles in classic Toho kaiju films, including several entries in the Godzilla and Mothra series.
-
B.
Jun’ya Koizumi
Jun’ya Koizumi is a Japanese politician and the son of former Prime Minister Junichiro Koizumi.
-
C.
Matajiro Koizumi
Matajiro Koizumi was a Japanese politician best known as the father of former Prime Minister Junichiro Koizumi and a member of the influential Koizumi political family.
-
D.
Hiroshi Satō
Hiroshi Satō is a Japanese given name commonly borne by men across various professions, including business, sports, and the arts.
-
E.
Hajime Koizumi
Hajime Koizumi was a Japanese cinematographer best known for his work on classic kaiju films, including entries in the Godzilla series.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4f52988190847230e119a35b87 |
completed | April 19, 2026, 2:13 a.m. |
Created at: April 10, 2026, 5:44 a.m.