Triple
T11864527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attendance Allowance |
E282247
|
entity |
| Predicate | rateBasis |
P49206
|
FINISHED |
| Object | based on level of care needed |
—
|
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: based on level of care needed | Statement: [Attendance Allowance, rateBasis, based on level of care needed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rateBasis Context triple: [Attendance Allowance, rateBasis, based on level of care needed]
-
A.
baseRate
Indicates the fundamental or standard rate at which something occurs or is charged, serving as a baseline before adjustments or modifiers are applied.
-
B.
fareBasis
Indicates the specific fare rule or pricing category that applies to a ticket or travel segment.
-
C.
rate
Indicates the numerical evaluation or assessment assigned by one entity to another based on perceived quality, performance, or value.
-
D.
calculationBasis
Indicates the rule, method, or reference standard used as the foundation for performing a calculation in the relationship.
-
E.
rateConvention
chosen
Indicates the standard, method, or set of rules used to determine or apply a particular rate (such as interest, tax, or pricing) in a given context.
- 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.