Triple

T18828867
Position Surface form Disambiguated ID Type / Status
Subject Jupyter Server E460468 entity
Predicate compatibleWith P203 FINISHED
Object Jupyter kernels 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: Jupyter kernels | Statement: [Jupyter Server, compatibleWith, Jupyter kernels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jupyter kernels
Context triple: [Jupyter Server, compatibleWith, Jupyter kernels]
  • A. Jupyter kernels chosen
    Jupyter kernels are modular computation backends that execute code in specific programming languages for Jupyter notebooks and other Jupyter frontends.
  • B. Jupyter Server
    Jupyter Server is the backend application that manages and serves Jupyter notebooks, kernels, and related services for frontends like JupyterLab.
  • C. Jupyter
    Jupyter is an open-source project that provides interactive computing tools, most notably Jupyter Notebooks, for data science, scientific computing, and education across multiple programming languages.
  • D. JupyterLab
    JupyterLab is a web-based interactive development environment for working with Jupyter notebooks, code, and data.
  • E. Jupyter Notebook
    Jupyter Notebook is an open-source web-based interactive computing environment that allows users to create and share documents containing live code, equations, visualizations, and narrative text.
  • 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_69d8dcf94c288190a06dea029ae4b223 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a99554848190933dd2810f5c810f completed April 20, 2026, 4:20 a.m.
Created at: April 10, 2026, 11:56 a.m.