Triple
T23836030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 石破茂 |
E590854
|
entity |
| Predicate | 政策スタンス |
P4795
|
FINISHED |
| Object | 安全保障に関する知識が豊富と評価される |
—
|
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: 安全保障に関する知識が豊富と評価される | Statement: [石破茂, 政策スタンス, 安全保障に関する知識が豊富と評価される]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 政策スタンス Context triple: [石破茂, 政策スタンス, 安全保障に関する知識が豊富と評価される]
-
A.
policyStance
chosen
Indicates the position or viewpoint an entity holds regarding a specific policy or set of policies.
-
B.
governmentStatus
Indicates the type or condition of governance or political authority that an entity currently holds or is subject to.
-
C.
policyResponseTo
Indicates a relationship where a policy is created, modified, or applied as a direct reaction to a specific event, condition, or prior action.
-
D.
policyApproach
Indicates the strategy, method, or overall course of action adopted in creating, implementing, or managing a policy.
-
E.
languagePolicyPosition
Indicates a stance or viewpoint an entity holds regarding rules, regulations, or practices governing language use.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c882f9148190bb28fe7566ef1e70 |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 8:07 p.m.