Triple
T18705485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubeflow Pipelines |
E457355
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Kubeflow Pipelines API server |
—
|
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 API server | Statement: [Kubeflow Pipelines, hasComponent, Kubeflow Pipelines API server]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kubeflow Pipelines API server Context triple: [Kubeflow Pipelines, hasComponent, Kubeflow Pipelines API server]
-
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.
Knative
Knative is an open-source Kubernetes-based platform that simplifies building, deploying, and managing serverless and event-driven applications.
-
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.
KEDA
KEDA is an open-source Kubernetes-based event-driven autoscaler that enables fine-grained, event-driven scaling of container workloads.
-
E.
Cloud Run
Cloud Run is a fully managed serverless compute platform from Google Cloud that runs containerized applications and APIs that scale automatically on demand.
- 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.