Triple

T4326124
Position Surface form Disambiguated ID Type / Status
Subject JointGrid E96637 entity
Predicate partOf P40 FINISHED
Object seaborn.axisgrid module E96637 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: seaborn.axisgrid module | Statement: [JointGrid, partOf, seaborn.axisgrid module]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: seaborn.axisgrid module
Context triple: [JointGrid, partOf, seaborn.axisgrid module]
  • A. JointGrid chosen
    JointGrid is a Seaborn plotting object that creates multi-panel visualizations combining joint and marginal distributions of two variables.
  • 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. TkAgg
    TkAgg is a Matplotlib backend that renders plots using the Agg engine and displays them in GUI windows via the Tkinter toolkit.
  • D. Matplotlib
    Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
  • 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.

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_69b5d09861a4819086a88bb42a8ea2e4 completed March 14, 2026, 9:18 p.m.
Created at: March 12, 2026, 11:13 p.m.