Triple

T1636541
Position Surface form Disambiguated ID Type / Status
Subject Kubernetes E35369 entity
Predicate ecosystem P964 FINISHED
Object Flux
Flux is a GitOps-based continuous delivery tool for Kubernetes that automates deploying and reconciling application state from version-controlled configuration.
 E184363 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: Flux | Statement: [Kubernetes, ecosystem, Flux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Flux
Context triple: [Kubernetes, ecosystem, Flux]
  • A. Lightwater
    Lightwater is a village and civil parish in the English county of Surrey, known for its residential character and proximity to heathland and countryside.
  • B. Lumo
    Lumo is a British open-access train operator running low-cost, long-distance electric services on the East Coast Main Line between London and northeastern England.
  • C. Dynamo
    Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
  • D. Flen
    Flen is a small Swedish town known as the administrative center of Flen Municipality in the province of Södermanland.
  • E. Blix
    Blix is a Swedish surname most notably associated with Hans Blix, the former head of the International Atomic Energy Agency and UN weapons inspector.
  • 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: Flux
Triple: [Kubernetes, ecosystem, Flux]
Generated description
Flux is a GitOps-based continuous delivery tool for Kubernetes that automates deploying and reconciling application state from version-controlled configuration.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Flux
Target entity description: Flux is a GitOps-based continuous delivery tool for Kubernetes that automates deploying and reconciling application state from version-controlled configuration.
  • A. Lightwater
    Lightwater is a village and civil parish in the English county of Surrey, known for its residential character and proximity to heathland and countryside.
  • B. Lumo
    Lumo is a British open-access train operator running low-cost, long-distance electric services on the East Coast Main Line between London and northeastern England.
  • C. Dynamo
    Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
  • D. Flen
    Flen is a small Swedish town known as the administrative center of Flen Municipality in the province of Södermanland.
  • E. Blix
    Blix is a Swedish surname most notably associated with Hans Blix, the former head of the International Atomic Energy Agency and UN weapons inspector.
  • 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_69a90a192d588190bbfa4693ed787c05 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.