Triple
T6337614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 重光 葵 |
E142529
|
entity |
| Predicate | 歴史的評価 |
P675
|
FINISHED |
| Object | 日本の降伏を象徴する人物の一人 |
—
|
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: 日本の降伏を象徴する人物の一人 | Statement: [重光 葵, 歴史的評価, 日本の降伏を象徴する人物の一人]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 歴史的評価 Context triple: [重光 葵, 歴史的評価, 日本の降伏を象徴する人物の一人]
-
A.
historicalAssessment
chosen
Indicates an evaluation or judgment of something based on its historical context, significance, or development over time.
-
B.
historicallyReevaluatedIn
Indicates that something has undergone a later historical reassessment or reinterpretation within a specified context or period.
-
C.
historicallyConsidered
Indicates that one entity has been regarded or classified in a particular way relative to another entity during a past historical period.
-
D.
historicalImpact
Indicates the influence or lasting effects that an entity, event, or action has had on subsequent history or historical developments.
-
E.
historical
Indicates that the subject has existed, occurred, or been relevant in the past rather than in the present or future.
- 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654e11988190b708426d3003716a |
completed | March 22, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69c060e7e2d48190af9d004236466788 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:30 p.m.