Triple
T8409170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canada Pension Plan |
E198577
|
entity |
| Predicate | deathBenefitType |
P81841
|
FINISHED |
| Object | one-time lump-sum payment |
—
|
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: one-time lump-sum payment | Statement: [Canada Pension Plan, deathBenefitType, one-time lump-sum payment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathBenefitType Context triple: [Canada Pension Plan, deathBenefitType, one-time lump-sum payment]
-
A.
benefitProtection
Indicates that one entity provides protective advantages or safeguards that benefit another entity.
-
B.
maximumLifetimeBenefit
Indicates the greatest total amount of benefit that can be received over the entire duration of eligibility or coverage.
-
C.
benefitStructure
Indicates a relationship where one entity defines, organizes, or governs the benefits (such as advantages, compensations, or perks) provided to or associated with another entity.
-
D.
insuranceType
Indicates the specific category or kind of insurance coverage associated with an entity or relationship.
-
E.
isIndividualBenefit
Indicates that something provides a benefit or advantage to a single individual rather than to a group or collective.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8317045c8190b69cc99854b633be |
completed | March 31, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76da264881909483b835e1db06da |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6:05 p.m.