Triple
T18705491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubeflow Pipelines |
E457355
|
entity |
| Predicate | uses |
P98
|
FINISHED |
| Object | Argo Workflows |
—
|
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: Argo Workflows | Statement: [Kubeflow Pipelines, uses, Argo Workflows]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argo Workflows Context triple: [Kubeflow Pipelines, uses, Argo Workflows]
-
A.
Argo Workflows
chosen
Argo Workflows is a Kubernetes-native workflow engine for orchestrating complex container-based jobs and CI/CD pipelines using declarative YAML.
-
B.
Argo Rollouts
Argo Rollouts is a Kubernetes controller and set of CRDs that provide advanced deployment strategies such as blue-green and canary releases with traffic management and progressive delivery features.
-
C.
Argo CD
Argo CD is a declarative, GitOps-based continuous delivery tool that automates application deployment and lifecycle management on Kubernetes clusters.
-
D.
Kubeflow Pipelines
Kubeflow Pipelines is a platform for building, deploying, and managing end-to-end machine learning workflows on Kubernetes using containerized components.
-
E.
Ray Workflows
Ray Workflows is a component of the Ray ecosystem that enables the definition, orchestration, and execution of complex, distributed workflows for machine learning and data processing.
- 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.