Triple

T4277709
Position Surface form Disambiguated ID Type / Status
Subject TkAgg E97081 entity
Predicate requires P100 FINISHED
Object Tkinter
Tkinter is Python’s standard GUI toolkit, providing a simple interface to the Tk GUI library for building desktop applications.
 E428634 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: Tkinter | Statement: [TkAgg, requires, Tkinter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tkinter
Context triple: [TkAgg, requires, Tkinter]
  • A. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • B. Jython
    Jython is an implementation of the Python programming language that runs on the Java platform and allows seamless integration with Java code and libraries.
  • 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. Tcl
    Tcl (Tool Command Language) is a high-level, embeddable scripting language widely used for rapid prototyping, GUI development (often with Tk), and extending applications.
  • 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. 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: Tkinter
Triple: [TkAgg, requires, Tkinter]
Generated description
Tkinter is Python’s standard GUI toolkit, providing a simple interface to the Tk GUI library for building desktop applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tkinter
Target entity description: Tkinter is Python’s standard GUI toolkit, providing a simple interface to the Tk GUI library for building desktop applications.
  • A. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • B. Jython
    Jython is an implementation of the Python programming language that runs on the Java platform and allows seamless integration with Java code and libraries.
  • 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. Tcl
    Tcl (Tool Command Language) is a high-level, embeddable scripting language widely used for rapid prototyping, GUI development (often with Tk), and extending applications.
  • 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. 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501ef1388190b0c968b069014a59 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7237b608190ab5aca56027344c4 completed March 14, 2026, 8:37 p.m.
NEDg Description generation batch_69b5c7bd187c8190b79894c864ea5b19 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c88035dc8190beacf43974a29c78 completed March 14, 2026, 8:43 p.m.
Created at: March 12, 2026, 11:07 p.m.