Triple
T25064693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SREN |
E627752
|
entity |
| Predicate | associatedCompanyRoleInIndustry |
P117326
|
FINISHED |
| Object | one of the world’s largest reinsurance companies |
—
|
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: one of the world’s largest reinsurance companies | Statement: [SREN, associatedCompanyRoleInIndustry, one of the world’s largest reinsurance companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCompanyRoleInIndustry Context triple: [SREN, associatedCompanyRoleInIndustry, one of the world’s largest reinsurance companies]
-
A.
hasIndustryRole
chosen
Indicates that an entity holds or performs a specific role, function, or position within a particular industry or sector.
-
B.
associatedCompanySpecialization
Indicates that a company is linked to a particular area of specialization or expertise.
-
C.
associatedCompanyNotableRole
Indicates that an entity has a notable role or position in a specified associated company.
-
D.
relationToIndustry
Indicates how an entity is connected or relevant to a particular industry, such as through involvement, impact, or association.
-
E.
roleInIndustry
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 18, 2026, 6:10 a.m.