Triple
T28528821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Directorate General for Public Administration |
E721983
|
entity |
| Predicate | hasStaffCategory |
P127311
|
FINISHED |
| Object | civil servants |
—
|
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: civil servants | Statement: [National Directorate General for Public Administration, hasStaffCategory, civil servants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffCategory Context triple: [National Directorate General for Public Administration, hasStaffCategory, civil servants]
-
A.
usesStaffCategory
chosen
Indicates that an entity employs or applies a particular category or classification of staff in its operations or context.
-
B.
hadStaffRole
Indicates that an entity served in a specific staff role or position for another entity during some period.
-
C.
hasStaffingStatus
Indicates the current staffing condition or level associated with an entity, such as whether it is adequately, under-, or over-staffed.
-
D.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
E.
hasCategoryGroup
Indicates that something is associated with, or belongs to, a broader grouping of related categories.
- 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_69f01a5d7ec88190ada2d5be7c06c35d |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: April 28, 2026, 3:27 a.m.