Triple
T11874108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Statutory Pension Insurance |
E282479
|
entity |
| Predicate | socialRiskCovered |
P101985
|
FINISHED |
| Object | old age |
—
|
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: old age | Statement: [German Statutory Pension Insurance, socialRiskCovered, old age]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialRiskCovered Context triple: [German Statutory Pension Insurance, socialRiskCovered, old age]
-
A.
securityCapitalizationCoverage
Indicates the extent to which a security’s market capitalization is represented, included, or covered within a given dataset, index, or analytical scope.
-
B.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
C.
riskAddressed
Indicates that a particular risk has been identified and is being mitigated, managed, or otherwise handled by an associated action, control, or measure.
-
D.
securityTypeCoverage
Indicates the type or category of security that is covered or included under a given coverage or policy.
-
E.
riskTypesManaged
Indicates that one entity is responsible for handling, controlling, or overseeing specific categories of risk associated with another entity or context.
- 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.