Triple
T14168606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 伊藤 清 |
E351143
|
entity |
| Predicate | 影響分野 |
P52396
|
FINISHED |
| Object | 金融数学 |
—
|
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: 金融数学 | Statement: [伊藤 清, 影響分野, 金融数学]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 影響分野 Context triple: [伊藤 清, 影響分野, 金融数学]
-
A.
impactOnSubject
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
-
B.
業績の影響
Indicates that one entity’s performance or results have an effect on, or bring about changes in, another entity or outcome.
-
C.
influencedPolicyArea
Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
-
D.
impactOnField
chosen
Indicates the effect or influence that one entity, action, or development has on a particular field or domain.
-
E.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b355f08190864c7322bbcb766d |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1 a.m.