Triple
T18799748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PyQt5 |
E459729
|
entity |
| Predicate | hasModule |
P12988
|
FINISHED |
| Object |
PyQt5.QtMultimedia
PyQt5.QtMultimedia is a PyQt5 module that provides classes and functionality for handling audio, video, and multimedia content in Qt-based Python applications.
|
E1342449
|
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: PyQt5.QtMultimedia | Statement: [PyQt5, hasModule, PyQt5.QtMultimedia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PyQt5.QtMultimedia Context triple: [PyQt5, hasModule, PyQt5.QtMultimedia]
-
A.
PyQt5 or PySide2
PyQt5 or PySide2 are Python bindings for the Qt5 application framework, commonly used to create cross-platform graphical user interfaces.
-
B.
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.
-
C.
MediaPlayer
MediaPlayer is a JavaFX class that provides high-level controls for playing and managing audio and video media within Java 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.
GStreamer
GStreamer is an open-source multimedia framework used to build complex audio and video processing pipelines across multiple platforms.
- 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: PyQt5.QtMultimedia Triple: [PyQt5, hasModule, PyQt5.QtMultimedia]
Generated description
PyQt5.QtMultimedia is a PyQt5 module that provides classes and functionality for handling audio, video, and multimedia content in Qt-based Python applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PyQt5.QtMultimedia Target entity description: PyQt5.QtMultimedia is a PyQt5 module that provides classes and functionality for handling audio, video, and multimedia content in Qt-based Python applications.
-
A.
PyQt5 or PySide2
PyQt5 or PySide2 are Python bindings for the Qt5 application framework, commonly used to create cross-platform graphical user interfaces.
-
B.
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.
-
C.
MediaPlayer
MediaPlayer is a JavaFX class that provides high-level controls for playing and managing audio and video media within Java 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.
GStreamer
GStreamer is an open-source multimedia framework used to build complex audio and video processing pipelines across multiple platforms.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02273b481909bc250144a0ace32 |
completed | April 20, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a054723def4819097961a04087a54a3 |
completed | May 14, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_6a0549358ba081909eb649898d1b3a8a |
completed | May 14, 2026, 4:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0549c825f481909d2da63688b36186 |
completed | May 14, 2026, 4:04 a.m. |
Created at: April 10, 2026, 11:53 a.m.