Triple

T4600011
Position Surface form Disambiguated ID Type / Status
Subject Qt5Agg E100299 entity
Predicate compatibleWith P203 FINISHED
Object PySide2
PySide2 is the official Python binding for the Qt 5 application framework, enabling the creation of cross-platform graphical user interfaces.
 E459731 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: PySide2 | Statement: [Qt5Agg, compatibleWith, PySide2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PySide2
Context triple: [Qt5Agg, compatibleWith, PySide2]
  • A. 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.
  • B. Qt
    Qt is a cross-platform application development framework widely used for building graphical user interfaces and multi-platform software in C++.
  • C. Tkinter
    Tkinter is Python’s standard GUI toolkit, providing a simple interface to the Tk GUI library for building desktop applications.
  • D. QGIS
    QGIS is a free, open-source geographic information system application used for viewing, editing, and analyzing geospatial data across multiple platforms.
  • E. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • 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: PySide2
Triple: [Qt5Agg, compatibleWith, PySide2]
Generated description
PySide2 is the official Python binding for the Qt 5 application framework, enabling the creation of cross-platform graphical user interfaces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PySide2
Target entity description: PySide2 is the official Python binding for the Qt 5 application framework, enabling the creation of cross-platform graphical user interfaces.
  • A. 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.
  • B. Qt
    Qt is a cross-platform application development framework widely used for building graphical user interfaces and multi-platform software in C++.
  • C. Tkinter
    Tkinter is Python’s standard GUI toolkit, providing a simple interface to the Tk GUI library for building desktop applications.
  • D. QGIS
    QGIS is a free, open-source geographic information system application used for viewing, editing, and analyzing geospatial data across multiple platforms.
  • E. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • 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_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_69bdfa5a7aac8190b540b80816d55051 completed March 21, 2026, 1:54 a.m.
NEDg Description generation batch_69bdfb37b1448190a4001b9ed2b79012 completed March 21, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_69bdfc0e456c81908efa3858d981ccc0 completed March 21, 2026, 2:01 a.m.
Created at: March 20, 2026, 1:11 p.m.