Triple

T22907094
Position Surface form Disambiguated ID Type / Status
Subject Ayushman Bharat Pradhan Mantri Jan Arogya Yojana E568476 entity
Predicate benefitPackageType P75212 FINISHED
Object hospitalisation 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: hospitalisation | Statement: [Ayushman Bharat Pradhan Mantri Jan Arogya Yojana, benefitPackageType, hospitalisation]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: benefitPackageType
Context triple: [Ayushman Bharat Pradhan Mantri Jan Arogya Yojana, benefitPackageType, hospitalisation]
  • A. benefitStructure
    Indicates a relationship where one entity defines, organizes, or governs the benefits (such as advantages, compensations, or perks) provided to or associated with another entity.
  • B. benefitAppliesTo
    Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
  • C. hasBenefitType chosen
    Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
  • D. benefitsOrganizationType
    Indicates that something provides an advantage, support, or positive impact specifically to a particular type or category of organization.
  • E. benefitsLevel
    Indicates the degree or extent to which one entity gains advantages, support, or positive outcomes from another entity or action.
  • 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_69e2458cd9e48190943ad2e34485d939 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1801a48948190b5f51f1d02351fc7 completed April 29, 2026, 3:50 a.m.
PD Predicate disambiguation batch_69ef3b6b2e2481908258156937b5a745 completed April 27, 2026, 10:33 a.m.
Created at: April 17, 2026, 3:41 p.m.