Triple
T11874137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Statutory Pension Insurance |
E282479
|
entity |
| Predicate | policySupervisionFunction |
P101986
|
FINISHED |
| Object | oversight of contribution and benefit rules |
—
|
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: oversight of contribution and benefit rules | Statement: [German Statutory Pension Insurance, policySupervisionFunction, oversight of contribution and benefit rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policySupervisionFunction Context triple: [German Statutory Pension Insurance, policySupervisionFunction, oversight of contribution and benefit rules]
-
A.
policyTool
Indicates that an entity is a tool, mechanism, or instrument used to design, implement, or enforce a policy.
-
B.
policyImplication
Indicates that one policy, decision, or condition leads to, justifies, or necessitates another policy outcome or course of action.
-
C.
policyElement
Indicates that something is a component or constituent part of a broader policy.
-
D.
policyRequirement
Indicates that one entity specifies a rule, condition, or obligation that another entity must satisfy according to a policy.
-
E.
analyzesPolicyTool
Indicates that one entity examines, evaluates, or studies a policy-related tool or instrument to understand its features, effectiveness, or implications.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:43 p.m.