Triple
T313938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Readiness Brigades |
E7665
|
entity |
| Predicate | personnelType |
P11881
|
FINISHED |
| Object | conscripts and reservists with professional cadre |
—
|
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: conscripts and reservists with professional cadre | Statement: [Readiness Brigades, personnelType, conscripts and reservists with professional cadre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personnelType Context triple: [Readiness Brigades, personnelType, conscripts and reservists with professional cadre]
-
A.
peakPersonnel
Indicates the maximum number of personnel involved or present at any point during a specified period or activity.
-
B.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
C.
departmentType
Indicates the classification or category of a department, specifying what kind of department it is.
-
D.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
E.
participantType
Indicates the specific role or category that a participant has within a given event, activity, or relationship.
- F. None of above. chosen
Provenance (4 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea4bd6a081909bdb57602c7093b4 |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e9428098819089d5950cd2c96dc4 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:07 p.m.