Triple
T33791336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Globe Life And Accident Insurance Company |
E865937
|
entity |
| Predicate | riskTypeInsured |
P15871
|
FINISHED |
| Object | mortality risk |
—
|
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: mortality risk | Statement: [Globe Life And Accident Insurance Company, riskTypeInsured, mortality risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskTypeInsured Context triple: [Globe Life And Accident Insurance Company, riskTypeInsured, mortality risk]
-
A.
riskType
chosen
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
B.
riskTypesManaged
Indicates that one entity is responsible for handling, controlling, or overseeing specific categories of risk associated with another entity or context.
-
C.
riskCoverage
Indicates the extent to which a particular risk is protected against, mitigated, or compensated for by a policy, measure, or arrangement.
-
D.
riskTakenFor
Indicates that one entity accepts or undertakes a risk for the benefit, protection, or sake of another entity.
-
E.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
- 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_69f3498f99f481909cb271f4965a7594 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:45 a.m.