Triple
T3705357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkshire Hathaway Primary Group |
E80877
|
entity |
| Predicate | riskTypeCovered |
P15871
|
FINISHED |
| Object | property 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: property risk | Statement: [Berkshire Hathaway Primary Group, riskTypeCovered, property risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskTypeCovered Context triple: [Berkshire Hathaway Primary Group, riskTypeCovered, property 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.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
D.
riskAddressed
Indicates that a particular risk has been identified and is being mitigated, managed, or otherwise handled by an associated action, control, or measure.
-
E.
riskFeature
Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54bbfcc8190bec9c16e3749c3b1 |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.