Triple
T8780444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 岡村寧次 |
E208710
|
entity |
| Predicate | 軍事的専門分野 |
P17742
|
FINISHED |
| Object | 対中国作戦指導 |
—
|
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: 対中国作戦指導 | Statement: [岡村寧次, 軍事的専門分野, 対中国作戦指導]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 軍事的専門分野 Context triple: [岡村寧次, 軍事的専門分野, 対中国作戦指導]
-
A.
militaryDomain
chosen
Indicates that the relationship or action occurs within, pertains to, or is specifically associated with the military sphere or context.
-
B.
militaryFunction
Indicates a relationship where an entity serves a specific role, duty, or operational purpose within a military context.
-
C.
militaryContext
Indicates that the relationship or action occurs within a military setting, framework, or operational environment.
-
D.
countryMilitary
Indicates that a country possesses, controls, or is associated with a particular military force or armed organization.
-
E.
militaryUse
Indicates the use of something (such as land, facilities, equipment, or resources) for military purposes or operations.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f548aa48190b2e73f292758e361 |
completed | March 31, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:42 p.m.