Triple
T21461813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 陸軍次官 |
E529489
|
entity |
| Predicate | 関連役職 |
P21749
|
FINISHED |
| Object | 陸軍大臣 |
—
|
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: 陸軍大臣 | Statement: [陸軍次官, 関連役職, 陸軍大臣]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連役職 Context triple: [陸軍次官, 関連役職, 陸軍大臣]
-
A.
roleSimilarTo
chosen
Indicates that two entities have roles or functions that are alike or closely comparable in nature or responsibility.
-
B.
roleInPersonnelMatters
Indicates that one entity has a specific function, authority, or involvement in managing or deciding personnel-related matters concerning another entity.
-
C.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
D.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
E.
associatedWorkType
Indicates the type or category of work with which an entity is associated (e.g., publication, artwork, performance).
- 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9ef0c0881908554977df00604a6 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:09 p.m.