Triple

T18800822
Position Surface form Disambiguated ID Type / Status
Subject AWS CDK E459748 entity
Predicate supportsService P203 FINISHED
Object AWS Budgets NE NERFINISHED

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: AWS Budgets | Statement: [AWS CDK, supportsService, AWS Budgets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AWS Budgets
Context triple: [AWS CDK, supportsService, AWS Budgets]
  • A. AWS Budgets chosen
    AWS Budgets is an Amazon Web Services tool that lets users set custom cost and usage budgets, receive alerts, and track spending against financial targets in the cloud.
  • B. AWS Cost Explorer
    AWS Cost Explorer is a cloud cost management tool that helps users visualize, analyze, and optimize their AWS spending over time.
  • C. Azure Cost Management + Billing
    Azure Cost Management + Billing is a set of Azure tools and services that help organizations monitor, analyze, and optimize their cloud spending and manage billing across subscriptions and accounts.
  • D. BudgetService
    BudgetService is a component of the Google AdWords API that manages and configures advertising campaign budgets programmatically.
  • E. AWS Compute Optimizer
    AWS Compute Optimizer is an Amazon Web Services tool that analyzes resource usage to recommend optimal compute configurations for cost savings and performance improvements.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a02332d88190b68feea7f2f86d06 completed April 20, 2026, 3:40 a.m.
Created at: April 10, 2026, 11:53 a.m.