Triple
T33643716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pradhan Mantri Fasal Bima Yojana |
E861899
|
entity |
| Predicate | claimSettlementBasis |
P141562
|
FINISHED |
| Object | yield loss assessment |
—
|
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: yield loss assessment | Statement: [Pradhan Mantri Fasal Bima Yojana, claimSettlementBasis, yield loss assessment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: claimSettlementBasis Context triple: [Pradhan Mantri Fasal Bima Yojana, claimSettlementBasis, yield loss assessment]
-
A.
reasonForSettlement
Indicates the underlying cause, motivation, or circumstance that led to a settlement being made.
-
B.
indemnityBasis
chosen
Indicates that one party’s obligation to compensate another for loss, damage, or liability is determined according to a specified indemnification standard or method.
-
C.
decisionBasis
Indicates the underlying reason, criterion, or rationale on which a decision is made.
-
D.
wasSettledBy
Indicates that a place or region came to be inhabited or established through the actions of a particular person, group, or population.
-
E.
settlementType
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 1, 2026, 1:42 a.m.