Triple
T9807478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregon ABLE Savings Plan |
E238187
|
entity |
| Predicate | qualifiedExpenseType |
P62936
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [Oregon ABLE Savings Plan, qualifiedExpenseType, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: qualifiedExpenseType Context triple: [Oregon ABLE Savings Plan, qualifiedExpenseType, education]
-
A.
reimbursementCategory
Indicates the classification or type under which a reimbursement claim or expense is categorized.
-
B.
programCostType
Indicates the type or category of cost associated with a program.
-
C.
exemptionType
Indicates the specific category or kind of exemption that applies in a given context.
-
D.
mainExpenditureCategory
chosen
Indicates the primary type or classification of spending to which a particular expenditure mainly belongs.
-
E.
chargeType
Indicates the category or nature of a charge applied in a transaction or interaction between entities (e.g., fee type, billing classification, or legal charge type).
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7ddaac8190a5584a5c863fbaa3 |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.