Triple
T11864620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carer’s Credit |
E282249
|
entity |
| Predicate | affectsStatePensionAmount |
P63442
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Carer’s Credit, affectsStatePensionAmount, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsStatePensionAmount Context triple: [Carer’s Credit, affectsStatePensionAmount, yes]
-
A.
pensionAmount
Indicates the specific monetary value of a pension that is assigned to or received by an entity.
-
B.
pensionIssue
Indicates that an entity is involved in the granting, receiving, managing, or disputing of a pension or retirement-benefit payment.
-
C.
receivesPensionFrom
Indicates that one entity is the source or provider of a pension that another entity receives.
-
D.
affectsBenefit
chosen
Indicates that one entity has an influence on, modifies, or determines the benefit or advantage received by another entity.
-
E.
mayAffectEligibility
Indicates that one entity has the potential to change, positively or negatively, another entity’s qualification or eligibility status for something.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73883508190a78b5f4ba4a220df |
completed | April 10, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.