Triple
T2606140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Weather Payment |
E58661
|
entity |
| Predicate | hasEligibilityCategory |
P19816
|
FINISHED |
| Object | income-related benefits claimants |
—
|
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: income-related benefits claimants | Statement: [Cold Weather Payment, hasEligibilityCategory, income-related benefits claimants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEligibilityCategory Context triple: [Cold Weather Payment, hasEligibilityCategory, income-related benefits claimants]
-
A.
eligibilityCategory
chosen
Indicates the classification or type of eligibility that applies to an entity within a given context.
-
B.
eligibilityLevel
Indicates the degree or tier of qualification an entity has for a given benefit, service, or status.
-
C.
eligibilityContext
Indicates the situational or conditional factors under which an entity qualifies for or is considered eligible for something.
-
D.
eligibility
Indicates that an entity meets the required conditions or qualifications to participate in, receive, or perform something.
-
E.
positionEligible
Indicates that an entity is qualified or permitted to hold or be assigned to a particular position or role.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.