Triple
T9001030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony Life Insurance |
E215037
|
entity |
| Predicate | hasRiskType |
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: [Sony Life Insurance, hasRiskType, mortality risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiskType Context triple: [Sony Life Insurance, hasRiskType, mortality risk]
-
A.
riskType
chosen
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
B.
hasHazardLevel
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
C.
hasWithdrawalRisk
Indicates that discontinuing or reducing something is associated with a risk of withdrawal effects or adverse reactions.
-
D.
riskTypesManaged
Indicates that one entity is responsible for handling, controlling, or overseeing specific categories of risk associated with another entity or context.
-
E.
hasCountryOfRisk
Indicates that an entity is associated with a country where it faces significant exposure, vulnerability, or potential risk.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6954bb1881908d004a26ba7fe360 |
completed | April 1, 2026, 12:39 a.m. |
| PD | Predicate disambiguation | batch_69cc5edd6cb48190b4fc6d6ca0418056 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:05 p.m.