Triple

T18705486
Position Surface form Disambiguated ID Type / Status
Subject Kubeflow Pipelines E457355 entity
Predicate hasComponent P35 FINISHED
Object Kubeflow Pipelines UI 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: Kubeflow Pipelines UI | Statement: [Kubeflow Pipelines, hasComponent, Kubeflow Pipelines UI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kubeflow Pipelines UI
Context triple: [Kubeflow Pipelines, hasComponent, Kubeflow Pipelines UI]
  • A. Kubeflow Pipelines chosen
    Kubeflow Pipelines is a platform for building, deploying, and managing end-to-end machine learning workflows on Kubernetes using containerized components.
  • B. SageMaker Studio
    SageMaker Studio is Amazon SageMaker’s web-based integrated development environment (IDE) for building, training, and deploying machine learning models at scale.
  • C. Argo Workflows
    Argo Workflows is a Kubernetes-native workflow engine for orchestrating complex container-based jobs and CI/CD pipelines using declarative YAML.
  • D. Weights & Biases
    Weights & Biases is a machine learning experiment tracking and model management platform that helps teams monitor, visualize, and optimize their ML workflows.
  • E. LibreView cloud platform
    LibreView cloud platform is a web-based diabetes management system that stores, analyzes, and shares glucose data from FreeStyle Libre devices for patients and healthcare providers.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671665bc8190b9b4a4ce4ec5b2eb completed April 19, 2026, 11:36 p.m.
Created at: April 10, 2026, 11:49 a.m.