Triple
T7526059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Series I savings bonds |
E177894
|
entity |
| Predicate | interestAccrualFrequency |
P41187
|
FINISHED |
| Object | monthly |
—
|
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: monthly | Statement: [Series I savings bonds, interestAccrualFrequency, monthly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interestAccrualFrequency Context triple: [Series I savings bonds, interestAccrualFrequency, monthly]
-
A.
interestRateResetFrequency
Indicates how often the applicable interest rate is recalculated or adjusted over the life of a financial agreement.
-
B.
payFrequency
chosen
Indicates how often a payment or series of payments is made within a given time period.
-
C.
maximumAccrualPeriod
Indicates the longest time span over which something (such as interest, benefits, or rights) can accumulate before it stops accruing.
-
D.
accrualUnit
Indicates the unit of measure (such as days, months, or years) in which something accumulates or is accrued over time.
-
E.
effectOnTotalInterest
Indicates how a given factor or action changes the overall amount of interest accrued or owed.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c7ac5c8190bbf9befdff791de0 |
completed | March 27, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.