Triple
T702591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RKKA |
E14029
|
entity |
| Predicate | usedConscription |
P4136
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [RKKA, usedConscription, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedConscription Context triple: [RKKA, usedConscription, yes]
-
A.
usesConscription
chosen
Indicates that a state or authority compels individuals into military or national service through mandatory conscription.
-
B.
commissionedIn
Indicates that an entity was formally requested or authorized to be created, produced, or carried out in a specific time period or location.
-
C.
militaryStatus
Indicates the relationship between an entity and a military organization in terms of service condition, such as active duty, reserve, veteran, or non-military status.
-
D.
militaryForceUsed
Indicates that one entity employs or applies military power or armed force against, within, or in relation to another entity or situation.
-
E.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58d4c3c8190ad4527d14bca5e6e |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4edc33881909a978268f6dd5d82 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.