Triple

T816614
Position Surface form Disambiguated ID Type / Status
Subject Matplotlib E17663 entity
Predicate usesBackend P4791 FINISHED
Object TkAgg
TkAgg is a Matplotlib backend that renders plots using the Agg engine and displays them in GUI windows via the Tkinter toolkit.
 E97081 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: TkAgg | Statement: [Matplotlib, usesBackend, TkAgg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TkAgg
Context triple: [Matplotlib, usesBackend, TkAgg]
  • A. Matplotlib
    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. thebe
    The thebe is the fractional monetary unit of Botswana, representing one-hundredth of a Botswana pula.
  • E. MATE desktop environment
    MATE desktop environment is a lightweight, traditional-style graphical user interface for Unix-like operating systems, continuing the classic GNOME 2 experience with ongoing updates and support.
  • 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: TkAgg
Triple: [Matplotlib, usesBackend, TkAgg]
Generated description
TkAgg is a Matplotlib backend that renders plots using the Agg engine and displays them in GUI windows via the Tkinter toolkit.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TkAgg
Target entity description: TkAgg is a Matplotlib backend that renders plots using the Agg engine and displays them in GUI windows via the Tkinter toolkit.
  • A. Matplotlib
    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. thebe
    The thebe is the fractional monetary unit of Botswana, representing one-hundredth of a Botswana pula.
  • E. MATE desktop environment
    MATE desktop environment is a lightweight, traditional-style graphical user interface for Unix-like operating systems, continuing the classic GNOME 2 experience with ongoing updates and support.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a78bd0a1d48190907434a17853dfb1 completed March 4, 2026, 1:33 a.m.
NED2 Entity disambiguation (via description) batch_69a78c3a57d88190a994ed44bcb2d8d1 completed March 4, 2026, 1:34 a.m.
Created at: March 1, 2026, 7:38 p.m.