Triple

T5894798
Position Surface form Disambiguated ID Type / Status
Subject Quasar Framework E131075 entity
Predicate hasComponent P35 FINISHED
Object QDialog
QDialog is a Quasar Framework UI component that provides customizable modal dialog windows for displaying content and interactions above the main interface.
E553109 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: QDialog | Statement: [Quasar Framework, hasComponent, QDialog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: QDialog
Context triple: [Quasar Framework, hasComponent, QDialog]
  • A. Qt
    Qt is a cross-platform application development framework widely used for building graphical user interfaces and multi-platform software in C++.
  • B. PyQt5 or PySide2
    PyQt5 or PySide2 are Python bindings for the Qt5 application framework, commonly used to create cross-platform graphical user interfaces.
  • C. QtWebKit
    QtWebKit is a port of the WebKit browser engine that integrates it with the Qt application framework for embedding web content in Qt-based applications.
  • D. PySide2
    PySide2 is the official Python binding for the Qt 5 application framework, enabling the creation of cross-platform graphical user interfaces.
  • 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: QDialog
Triple: [Quasar Framework, hasComponent, QDialog]
Generated description
QDialog is a Quasar Framework UI component that provides customizable modal dialog windows for displaying content and interactions above the main interface.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: QDialog
Target entity description: QDialog is a Quasar Framework UI component that provides customizable modal dialog windows for displaying content and interactions above the main interface.
  • A. Qt
    Qt is a cross-platform application development framework widely used for building graphical user interfaces and multi-platform software in C++.
  • B. PyQt5 or PySide2
    PyQt5 or PySide2 are Python bindings for the Qt5 application framework, commonly used to create cross-platform graphical user interfaces.
  • C. QtWebKit
    QtWebKit is a port of the WebKit browser engine that integrates it with the Qt application framework for embedding web content in Qt-based applications.
  • D. PySide2
    PySide2 is the official Python binding for the Qt 5 application framework, enabling the creation of cross-platform graphical user interfaces.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036f3364c81909353f62ca483f24f completed March 22, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b1558fa48190a6ecde69c1477863 completed March 23, 2026, 3:19 a.m.
NEDg Description generation batch_69c0b2442bf881908aeaecb46463e32d completed March 23, 2026, 3:23 a.m.
NED2 Entity disambiguation (via description) batch_69c0b2bc8b9c8190ab642d317056b1de completed March 23, 2026, 3:25 a.m.
Created at: March 22, 2026, 3:58 p.m.