Triple
T33643703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pradhan Mantri Fasal Bima Yojana |
E861899
|
entity |
| Predicate | unitOfInsurance |
P177460
|
FINISHED |
| Object | notified area |
—
|
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: notified area | Statement: [Pradhan Mantri Fasal Bima Yojana, unitOfInsurance, notified area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unitOfInsurance Context triple: [Pradhan Mantri Fasal Bima Yojana, unitOfInsurance, notified area]
-
A.
typeOfInsurer
Indicates the specific category or classification of an insurer in relation to an insurance policy or coverage.
-
B.
insuranceType
Indicates the specific category or kind of insurance coverage associated with an entity or relationship.
-
C.
insurance
Indicates a relationship where one party provides financial protection or coverage to another against specified risks or losses, typically in exchange for payment.
-
D.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
E.
designationUnit
Indicates that one entity serves as the unit or standard of measure used to designate, label, or quantify another entity.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb93224881908fc66fe76115fcdb |
completed | May 3, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fb17d5ec81909091e37e1ddbe577 |
completed | May 3, 2026, 7:36 a.m. |
Created at: May 1, 2026, 1:42 a.m.