Triple

T7933170
Position Surface form Disambiguated ID Type / Status
Subject Cloud Deploy E184229 entity
Predicate deploymentTarget P12960 FINISHED
Object Cloud Run E184211 NE 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: Cloud Run | Statement: [Cloud Deploy, deploymentTarget, Cloud Run]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cloud Run
Context triple: [Cloud Deploy, deploymentTarget, Cloud Run]
  • A. Cloud Run chosen
    Cloud Run is a fully managed serverless compute platform from Google Cloud that runs containerized applications and APIs that scale automatically on demand.
  • B. Cloud Functions
    Cloud Functions is Google Cloud’s serverless compute platform for running event-driven code without managing servers.
  • C. Knative
    Knative is an open-source Kubernetes-based platform that simplifies building, deploying, and managing serverless and event-driven applications.
  • D. Google Kubernetes Engine
    Google Kubernetes Engine is a managed Kubernetes service that lets users deploy, manage, and scale containerized applications on Google Cloud infrastructure.
  • E. Azure Container Instances
    Azure Container Instances is a Microsoft Azure service that lets you run Docker containers on demand in a fully managed, serverless environment without needing to provision or manage virtual machines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3acfd2a88190b1a13cd6fdedc272 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce01c37978819090922f7fc273edc9 completed April 2, 2026, 5:42 a.m.
Created at: March 30, 2026, 5:08 p.m.