Triple
T6245782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graduated Repayment Plan |
E139717
|
entity |
| Predicate | paymentIncreaseInterval |
P69283
|
FINISHED |
| Object | typically every two years |
—
|
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: typically every two years | Statement: [Graduated Repayment Plan, paymentIncreaseInterval, typically every two years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paymentIncreaseInterval Context triple: [Graduated Repayment Plan, paymentIncreaseInterval, typically every two years]
-
A.
migrationIncreasePeriod
Indicates a time span during which the level or rate of migration rises compared to a preceding period.
-
B.
paymentPeriodLength
Indicates the duration or length of time that each payment period covers in a recurring payment or billing schedule.
-
C.
settingPeriodDuration
Indicates the length of time for which a particular setting or configuration remains in effect.
-
D.
payFrequency
Indicates how often a payment or series of payments is made within a given time period.
-
E.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
- F. None of above. chosen
Provenance (4 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631d9e648190a59ab4001f506424 |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056df95ac8190bc5efe050d3af864 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:23 p.m.