Triple
T4766489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 池田勇人 |
E105823
|
entity |
| Predicate | 関連する出来事 |
P38977
|
FINISHED |
| Object | 日米安全保障条約改定後の政治安定化 |
—
|
LITERAL FINISHED |
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: 日米安全保障条約改定後の政治安定化 | Statement: [池田勇人, 関連する出来事, 日米安全保障条約改定後の政治安定化]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連する出来事 Context triple: [池田勇人, 関連する出来事, 日米安全保障条約改定後の政治安定化]
-
A.
laterRelatedEvent
Indicates that one event is temporally related to another by occurring at a later time.
-
B.
dateOfRelatedEvent
Indicates that there is a specific date on which a related event associated with the subject occurs or occurred.
-
C.
associatedEventType
chosen
Indicates that one entity is linked to another by the type or category of event with which it is associated.
-
D.
concernsEventsIn
Indicates a relationship where something (such as a statement, document, or discussion) is about, relates to, or addresses specific events occurring in a particular context or scope.
-
E.
関連主題
Indicates that there exists a thematically or contextually related subject connected to the given entity.
- F. None of above.
Provenance (3 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd686ef1b08190ad60375592c9d6c0 |
completed | March 20, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69bd622807f881908e4bcb14f7731bac |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.