Triple
T23836041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 石破茂 |
E590854
|
entity |
| Predicate | 主な関心分野 |
P44657
|
FINISHED |
| Object | 安全保障 |
—
|
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 | Statement: [石破茂, 主な関心分野, 安全保障]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 主な関心分野 Context triple: [石破茂, 主な関心分野, 安全保障]
-
A.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
-
B.
primaryInterest
chosen
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
-
C.
disciplinaryFocus
Indicates the primary academic or professional field, subject area, or discipline that something is centered on or concerned with.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
- 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.