Triple

T7938829
Position Surface form Disambiguated ID Type / Status
Subject kube-apiserver E184343 entity
Predicate communicatesWith P19362 FINISHED
Object etcd E184346 NE FINISHED

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: etcd | Statement: [kube-apiserver, communicatesWith, etcd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: etcd
Context triple: [kube-apiserver, communicatesWith, etcd]
  • A. etcd chosen
    etcd is a distributed, reliable key-value store commonly used as the backing data store for configuration and state management in systems like Kubernetes.
  • B. TiKV
    TiKV is an open-source, distributed transactional key-value database designed for horizontal scalability and strong consistency, often used as the storage layer for cloud-native applications.
  • C. CockroachDB
    CockroachDB is a distributed SQL database designed for horizontal scalability, strong consistency, and high fault tolerance across multiple nodes and regions.
  • D. OpenEBS
    OpenEBS is an open-source, cloud-native storage solution for Kubernetes that provides container-attached, software-defined storage for stateful applications.
  • E. Galera Cluster
    Galera Cluster is a synchronous multi-master replication solution that enables high-availability, fault-tolerant clustering for MySQL-compatible databases like MariaDB.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3af0a2048190838d1aeda59fda0b completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc564a4fac8190972f9dfa7c026ea8 completed March 31, 2026, 11:18 p.m.
Created at: March 30, 2026, 5:08 p.m.