Triple
T19833395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Kok cabinet |
E476520
|
entity |
| Predicate | healthcarePolicy |
P9227
|
FINISHED |
| Object | healthcare system adjustments |
—
|
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: healthcare system adjustments | Statement: [Second Kok cabinet, healthcarePolicy, healthcare system adjustments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthcarePolicy Context triple: [Second Kok cabinet, healthcarePolicy, healthcare system adjustments]
-
A.
healthcareAccess
Indicates the degree to which individuals can obtain and use needed health care services.
-
B.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
C.
healthSystem
Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
-
D.
effectOnHealthCare
Indicates the impact or influence that something has on the quality, accessibility, cost, or delivery of health care services.
-
E.
positionOnHealthCare
chosen
Indicates a person or entity’s stance, opinion, or policy preference regarding health care systems, services, or reforms.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656d0347c8190b586c7fe01b61e97 |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.