Triple

T18800824
Position Surface form Disambiguated ID Type / Status
Subject AWS CDK E459748 entity
Predicate supportsService P203 FINISHED
Object AWS X-Ray 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 X-Ray | Statement: [AWS CDK, supportsService, AWS X-Ray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AWS X-Ray
Context triple: [AWS CDK, supportsService, AWS X-Ray]
  • A. AWS X-Ray chosen
    AWS X-Ray is an AWS service that helps developers analyze and debug distributed applications by tracing requests as they travel through various microservices and resources.
  • B. Cloud Trace
    Cloud Trace is a Google Cloud service that collects and analyzes latency data from applications to help developers monitor, debug, and optimize performance.
  • C. Amazon CloudWatch
    Amazon CloudWatch is a monitoring and observability service that collects and analyzes logs, metrics, and events from AWS resources and applications to help track performance and operational health.
  • D. Amazon Inspector
    Amazon Inspector is an automated security assessment service from AWS that continuously scans workloads for vulnerabilities and unintended network exposure to help improve cloud security and compliance.
  • E. AppDynamics
    AppDynamics is an application performance monitoring and observability company that provides tools to track, analyze, and optimize the performance of software applications and IT infrastructure.
  • 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.