Triple

T20399362
Position Surface form Disambiguated ID Type / Status
Subject Hospital-Acquired Condition Reduction Program E500289 entity
Predicate incentiveMechanism P43683 FINISHED
Object financial penalties 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: financial penalties | Statement: [Hospital-Acquired Condition Reduction Program, incentiveMechanism, financial penalties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: incentiveMechanism
Context triple: [Hospital-Acquired Condition Reduction Program, incentiveMechanism, financial penalties]
  • A. rewardMechanism
    Indicates a relationship where an entity provides or defines a system of incentives or compensation in response to certain actions, behaviors, or outcomes.
  • B. ownerIncentive
    Indicates that an owner has a motivation, benefit, or reward associated with a particular entity, action, or outcome.
  • C. providesIncentivesTo
    Indicates that one entity offers rewards, benefits, or motivations to another entity to encourage a desired behavior or outcome.
  • D. economicMechanism chosen
    Indicates an economic process, structure, or set of rules through which resources, incentives, or transactions are organized and outcomes are generated.
  • E. rewardModel
    Indicates a relationship where one entity serves as a model or framework for assigning rewards or evaluating outcomes for another entity or process.
  • 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_69e0b4a81bec8190b69adfdc1336a015 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6798cf04481909f183c4c75fe6d52 completed April 20, 2026, 7:07 p.m.
PD Predicate disambiguation batch_69e5765d7cb48190adec18d6d1e3d263 completed April 20, 2026, 12:42 a.m.
Created at: April 16, 2026, 11:29 a.m.