Triple
T9938157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AET |
E194006
|
entity |
| Predicate | issuerProductType |
P48533
|
FINISHED |
| Object | medical 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: medical insurance | Statement: [AET, issuerProductType, medical insurance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: issuerProductType Context triple: [AET, issuerProductType, medical insurance]
-
A.
issuerType
Indicates the classification or category of the entity that issues something (such as a document, credential, or instrument).
-
B.
issuerProduces
Indicates that an issuer creates, generates, or brings into existence a particular product, document, asset, or item.
-
C.
issuerBrandPortfolioIncludes
Indicates that an issuer’s overall brand portfolio contains or encompasses a particular brand.
-
D.
issuerSpecialization
Indicates the particular field, domain, or area of expertise in which the issuer is specialized.
-
E.
typeOfInsurer
chosen
Indicates the specific category or classification of an insurer in relation to an insurance policy or coverage.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e64760819094f599f158d32f33 |
completed | April 2, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:44 p.m.