Triple
T12934664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BSC |
E309474
|
entity |
| Predicate | riskPerception |
P62537
|
FINISHED |
| Object | associated with high leverage and mortgage-related exposure |
—
|
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: associated with high leverage and mortgage-related exposure | Statement: [BSC, riskPerception, associated with high leverage and mortgage-related exposure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskPerception Context triple: [BSC, riskPerception, associated with high leverage and mortgage-related exposure]
-
A.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
-
B.
riskElement
chosen
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
C.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
D.
risk
Indicates that one entity is exposed or subject to potential harm, loss, or adverse outcome arising from another entity, action, or situation.
-
E.
riskLevel
Indicates the degree of potential harm, loss, or adverse outcome associated with a particular situation, action, or entity.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.