Triple
T22580788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 学習院大学政経学部 |
E544559
|
entity |
| Predicate | 教育目的 |
P102783
|
FINISHED |
| Object | 政治と経済に関する専門的知識を備えた人材の育成 |
—
|
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: 政治と経済に関する専門的知識を備えた人材の育成 | Statement: [学習院大学政経学部, 教育目的, 政治と経済に関する専門的知識を備えた人材の育成]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 教育目的 Context triple: [学習院大学政経学部, 教育目的, 政治と経済に関する専門的知識を備えた人材の育成]
-
A.
educationGoal
chosen
Indicates a relationship where an entity has a specific educational aim, objective, or intended learning outcome it is working toward.
-
B.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
-
C.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
D.
educationPolicy
Indicates a relationship where an authority or entity establishes, governs, or influences rules, strategies, or frameworks guiding an education system or educational practices.
-
E.
educationIdeal
Indicates that something is regarded as the optimal or most desirable standard, goal, or model in the context of education.
- 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15ff065308190bca9fb24b47757e6 |
completed | April 29, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69ee626e6bb08190ada4dd8b48cc0c43 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:53 p.m.