Triple

T4599965
Position Surface form Disambiguated ID Type / Status
Subject Python scientific stack E100298 entity
Predicate coreVisualizationLibrary P7266 FINISHED
Object Matplotlib E17663 NE FINISHED

How this triple was built (3 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: Matplotlib | Statement: [Python scientific stack, coreVisualizationLibrary, Matplotlib]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matplotlib
Context triple: [Python scientific stack, coreVisualizationLibrary, Matplotlib]
  • A. Matplotlib chosen
    Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
  • B. Seaborn
    Seaborn is a Python data visualization library built on top of Matplotlib that provides a high-level interface for creating attractive and informative statistical graphics.
  • C. Seaborn
    Seaborn is a masculine given name of English origin, historically used in colonial America and associated with individuals such as Seaborn Cotton.
  • D. Mayavi
    Mayavi is a 3D scientific data visualization library for Python, widely used for interactive plotting and analysis of complex numerical data.
  • E. Plotly
    Plotly is an interactive, open-source graphing and data visualization library widely used in Python for creating rich, web-based charts and dashboards.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: coreVisualizationLibrary
Context triple: [Python scientific stack, coreVisualizationLibrary, Matplotlib]
  • A. visualizationLibrary chosen
    Indicates that an entity uses, depends on, or is implemented with a particular visualization library for rendering or displaying visual data.
  • B. visualElements
    Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
  • C. graphics
    Indicates a relationship where one entity is responsible for creating, providing, or handling visual representations or graphical content for another entity or context.
  • D. chartDepiction
    Indicates that one entity is a chart that visually represents or depicts information about another entity.
  • E. coreShape
    Indicates that one entity serves as the primary or central shape or geometric form of another entity.
  • F. None of above.

Provenance (4 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_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5971f448819090f6e76c7d3ffc2d completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0349e89c8190a94e72bdc1e4e59f completed March 21, 2026, 2:32 a.m.
PD Predicate disambiguation batch_69bd522c811c81909aae4feadae33174 completed March 20, 2026, 1:57 p.m.
Created at: March 20, 2026, 1:11 p.m.