Triple
T1057594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwegian ministries |
E22831
|
entity |
| Predicate | employ |
P7
|
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: [Norwegian ministries, employ, civil servants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employ Context triple: [Norwegian ministries, employ, civil servants]
-
A.
employer
chosen
Indicates a relationship where one entity hires, pays, and oversees the work of another entity.
-
B.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
C.
employsForm
Indicates that an entity makes use of or applies a particular form or format in carrying out an action or function.
-
D.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
E.
employmentContext
Indicates the situational or organizational setting in which an employment relationship or work activity takes place.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4ba6e35ac8190802341c31bda0e3b |
completed | March 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69a4b7340a048190807363f19d17a58f |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.