Triple
T7189072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dai-ichi Life Insurance Company |
E167639
|
entity |
| Predicate | hasMainBusinessSegment |
P16009
|
FINISHED |
| Object | domestic life insurance |
—
|
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: domestic life insurance | Statement: [Dai-ichi Life Insurance Company, hasMainBusinessSegment, domestic life insurance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainBusinessSegment Context triple: [Dai-ichi Life Insurance Company, hasMainBusinessSegment, domestic life insurance]
-
A.
hasMajorBusinessLine
chosen
Indicates that an entity conducts a primary or significant line of business in a specified area, sector, or activity.
-
B.
hasBusinessDivision
Indicates that an organization includes or is composed of a specific business division as a subordinate unit.
-
C.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
D.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
-
E.
hasBusinessNode
Indicates that an entity is associated with, linked to, or represented by a specific business-related node within a business structure or network.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e3d9188190ba2792098d76fb86 |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:50 p.m.