Triple
T8609545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PyGObject |
E203882
|
entity |
| Predicate | compatibleWith |
P203
|
FINISHED |
| Object |
GStreamer
GStreamer is an open-source multimedia framework used to build complex audio and video processing pipelines across multiple platforms.
|
E745802
|
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: GStreamer | Statement: [PyGObject, compatibleWith, GStreamer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GStreamer Context triple: [PyGObject, compatibleWith, GStreamer]
-
A.
FFmpeg
FFmpeg is a widely used open-source multimedia framework for decoding, encoding, transcoding, streaming, and processing audio and video across numerous formats and platforms.
-
B.
VLC media player
VLC media player is a free, open-source, cross-platform multimedia player and framework known for playing a vast range of audio and video formats without needing additional codecs.
-
C.
VLC
VLC is the three-letter IATA airport code assigned to Valencia Airport in Spain.
-
D.
MPlayer
MPlayer is a free, open-source, cross-platform media player known for supporting a wide range of audio and video formats via command-line and GUI front-ends.
-
E.
DirectShow
DirectShow is a Microsoft multimedia framework and API used on Windows for capturing, processing, and playing audio and video streams.
- 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: GStreamer Triple: [PyGObject, compatibleWith, GStreamer]
Generated description
GStreamer is an open-source multimedia framework used to build complex audio and video processing pipelines across multiple platforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GStreamer Target entity description: GStreamer is an open-source multimedia framework used to build complex audio and video processing pipelines across multiple platforms.
-
A.
FFmpeg
FFmpeg is a widely used open-source multimedia framework for decoding, encoding, transcoding, streaming, and processing audio and video across numerous formats and platforms.
-
B.
VLC media player
VLC media player is a free, open-source, cross-platform multimedia player and framework known for playing a vast range of audio and video formats without needing additional codecs.
-
C.
VLC
VLC is the three-letter IATA airport code assigned to Valencia Airport in Spain.
-
D.
MPlayer
MPlayer is a free, open-source, cross-platform media player known for supporting a wide range of audio and video formats via command-line and GUI front-ends.
-
E.
DirectShow
DirectShow is a Microsoft multimedia framework and API used on Windows for capturing, processing, and playing audio and video streams.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ed77588190a872d22d9d1f7429 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea90dd93081908140ac0ce23be820 |
completed | April 2, 2026, 5:36 p.m. |
| NEDg | Description generation | batch_69ceaa2c34308190a3bc7717012fea9d |
completed | April 2, 2026, 5:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ceaae76d188190932826c9fd9f7f5f |
completed | April 2, 2026, 5:44 p.m. |
Created at: March 30, 2026, 6:25 p.m.