Triple
T3501400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Farm Insurance |
E73975
|
entity |
| Predicate | typeOfInsurer |
P48533
|
FINISHED |
| Object | multi-line insurer |
—
|
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: multi-line insurer | Statement: [State Farm Insurance, typeOfInsurer, multi-line insurer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfInsurer Context triple: [State Farm Insurance, typeOfInsurer, multi-line insurer]
-
A.
insuranceType
Indicates the specific category or kind of insurance coverage associated with an entity or relationship.
-
B.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
C.
typeOfDepositInsurance
Indicates the specific kind or category of deposit insurance that applies to a financial account or institution.
-
D.
lenderType
Indicates the classification or category of the lender involved in a lending relationship (e.g., bank, individual, institution).
-
E.
issuerType
Indicates the classification or category of the entity that issues something (such as a document, credential, or instrument).
- F. None of above. chosen
Provenance (4 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd5fbe8819091b61fa8df355f0c |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0cd8b0819099da300af09880da |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaef1037c819082c7af949ec85360 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:18 p.m.