Triple
T4894141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. savings banks |
E109631
|
entity |
| Predicate | interestRateRisk |
P26874
|
FINISHED |
| Object | exposed to interest rate risk due to mortgage-heavy portfolios |
—
|
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: exposed to interest rate risk due to mortgage-heavy portfolios | Statement: [U.S. savings banks, interestRateRisk, exposed to interest rate risk due to mortgage-heavy portfolios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interestRateRisk Context triple: [U.S. savings banks, interestRateRisk, exposed to interest rate risk due to mortgage-heavy portfolios]
-
A.
riskMeasure
Indicates a quantitative assessment of the level of risk associated with an entity, event, or situation.
-
B.
interestRateName
Indicates the specific label or designation used to identify a particular interest rate.
-
C.
riskBasis
chosen
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
D.
riskModel
Indicates a relationship where an entity serves as or is associated with a model used to assess, quantify, or manage risk for another entity or situation.
-
E.
riskBased
Indicates that something is determined, prioritized, or managed according to the level or assessment of risk involved.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.