Triple

T4326150
Position Surface form Disambiguated ID Type / Status
Subject JointGrid E96637 entity
Predicate dependsOn P100 FINISHED
Object matplotlib E17663 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: matplotlib | Statement: [JointGrid, dependsOn, matplotlib]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: matplotlib
Context triple: [JointGrid, dependsOn, 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. Plotly
    Plotly is an interactive, open-source graphing and data visualization library widely used in Python for creating rich, web-based charts and dashboards.
  • D. TkAgg
    TkAgg is a Matplotlib backend that renders plots using the Agg engine and displays them in GUI windows via the Tkinter toolkit.
  • E. Qt5Agg
    Qt5Agg is a Matplotlib rendering backend that combines the Qt5 GUI framework with the Anti-Grain Geometry (Agg) engine to display high-quality interactive plots.
  • 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_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3513020f481909ff2fec3934f3002 completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db98ae888190aac5b5b7839ae7dd completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:13 p.m.