Triple
T21685255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 寺内内閣 |
E535212
|
entity |
| Predicate | 米騒動への対応 |
P87232
|
FINISHED |
| Object | 軍隊出動による鎮圧 |
—
|
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: 軍隊出動による鎮圧 | Statement: [寺内内閣, 米騒動への対応, 軍隊出動による鎮圧]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 米騒動への対応 Context triple: [寺内内閣, 米騒動への対応, 軍隊出動による鎮圧]
-
A.
responseToProtests
chosen
Indicates how an individual, group, or institution reacts or takes action in relation to protests or demonstrations.
-
B.
enactedInResponseTo
Indicates that one action, policy, or measure was carried out as a direct reaction to a specific prior event, condition, or stimulus.
-
C.
mobilization
Indicates the process by which entities are organized, activated, or assembled to take coordinated action or move into a state of readiness.
-
D.
関与作戦
Indicates a relationship where an entity is involved in, participates in, or contributes to the execution of a specific operation or mission.
-
E.
organizedInResponseTo
Indicates that an action or event was arranged or carried out specifically as a reaction to a prior situation, event, or stimulus.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96ca668481909f53853c7a8ea811 |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:44 p.m.