Triple
T1429706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adobe Audition |
E30415
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Cool Edit Pro |
E30415
|
NE FINISHED |
How this triple was built (2 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: Cool Edit Pro | Statement: [Adobe Audition, formerName, Cool Edit Pro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cool Edit Pro Context triple: [Adobe Audition, formerName, Cool Edit Pro]
-
A.
Adobe Audition
chosen
Adobe Audition is a professional digital audio workstation software used for recording, editing, mixing, and restoring audio for music, film, and broadcast production.
-
B.
Final Cut Pro
Final Cut Pro is Apple's professional non-linear video editing software widely used for film, television, and content creation on macOS.
-
C.
Adobe Premiere Pro
Adobe Premiere Pro is a professional non-linear video editing software widely used in film, television, and online content production.
-
D.
Adobe Media Encoder
Adobe Media Encoder is a video and audio transcoding application from Adobe that lets users export, compress, and convert media into various formats for playback, broadcast, and online distribution.
-
E.
Steinberg
Steinberg is a German and Ashkenazi Jewish surname borne by numerous notable individuals across fields such as music, art, business, and politics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c4db2d7481908d241593d0e17d83 |
completed | March 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad016930ec8190ab3900d6f40c4aa0 |
completed | March 8, 2026, 4:56 a.m. |
Created at: March 1, 2026, 8 p.m.