Triple
T1636500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubernetes |
E35369
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object |
kubelet
kubelet is the primary node-level agent in Kubernetes responsible for managing pods and their containers on each worker node.
|
E184347
|
NE FINISHED |
How this triple was built (4 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: kubelet | Statement: [Kubernetes, component, kubelet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: kubelet Context triple: [Kubernetes, component, kubelet]
-
A.
Kubernetes
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications across clusters of machines.
-
B.
Azure Kubernetes Service
Azure Kubernetes Service is a managed container orchestration platform that simplifies deploying, scaling, and operating Kubernetes clusters in the Microsoft Azure cloud.
-
C.
LXD
LXD is a system container and virtual machine manager that provides a user-friendly, image-based way to run and manage Linux environments.
-
D.
Fedora CoreOS
Fedora CoreOS is an automatically updating, minimal, container-focused operating system designed for running containerized workloads at scale.
-
E.
Docker
Docker is an open-source platform that uses containerization to package, distribute, and run applications consistently across different computing environments.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: kubelet Triple: [Kubernetes, component, kubelet]
Generated description
kubelet is the primary node-level agent in Kubernetes responsible for managing pods and their containers on each worker node.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: kubelet Target entity description: kubelet is the primary node-level agent in Kubernetes responsible for managing pods and their containers on each worker node.
-
A.
Kubernetes
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications across clusters of machines.
-
B.
Azure Kubernetes Service
Azure Kubernetes Service is a managed container orchestration platform that simplifies deploying, scaling, and operating Kubernetes clusters in the Microsoft Azure cloud.
-
C.
LXD
LXD is a system container and virtual machine manager that provides a user-friendly, image-based way to run and manage Linux environments.
-
D.
Fedora CoreOS
Fedora CoreOS is an automatically updating, minimal, container-focused operating system designed for running containerized workloads at scale.
-
E.
Docker
Docker is an open-source platform that uses containerization to package, distribute, and run applications consistently across different computing environments.
- F. None of above. chosen
Provenance (5 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a17e8e08190afb78a953ab920ec |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58dbd0608190be207ab2bcdc9eef |
completed | March 8, 2026, 11:09 a.m. |
| NEDg | Description generation | batch_69ad5a625d088190bbacbb69a0569d49 |
completed | March 8, 2026, 11:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad5ae605f88190b5e42d7cf923e9bb |
completed | March 8, 2026, 11:17 a.m. |
Created at: March 4, 2026, 7:28 p.m.