Triple
T9245168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sander Dieleman |
E222172
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Deep learning techniques for music recommendation (doctoral work)
"Deep learning techniques for music recommendation (doctoral work)" is Sander Dieleman’s PhD thesis that pioneered the application of deep neural networks to improve automated music recommendation and discovery.
|
E786387
|
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: Deep learning techniques for music recommendation (doctoral work) | Statement: [Sander Dieleman, notableWork, Deep learning techniques for music recommendation (doctoral work)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deep learning techniques for music recommendation (doctoral work) Context triple: [Sander Dieleman, notableWork, Deep learning techniques for music recommendation (doctoral work)]
-
A.
Human Jukebox
Human Jukebox is the renowned marching band of Southern University, celebrated for its high-energy performances, intricate formations, and influential role in HBCU band culture.
-
B.
Deep Learning (book)
Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
-
C.
The Well-Tempered Synthesizer
The Well-Tempered Synthesizer is a pioneering 1969 electronic music album by Wendy Carlos that features Baroque and classical works performed on Moog synthesizers, helping to popularize synthesized music.
-
D.
Music Genome Project
The Music Genome Project is a comprehensive music analysis system that categorizes songs by hundreds of musical attributes to power personalized listening recommendations.
-
E.
Neural Filters
Neural Filters are Adobe Photoshop’s AI-powered tools that apply advanced, machine-learning-based adjustments and creative effects to images with minimal manual editing.
- 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: Deep learning techniques for music recommendation (doctoral work) Triple: [Sander Dieleman, notableWork, Deep learning techniques for music recommendation (doctoral work)]
Generated description
"Deep learning techniques for music recommendation (doctoral work)" is Sander Dieleman’s PhD thesis that pioneered the application of deep neural networks to improve automated music recommendation and discovery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Deep learning techniques for music recommendation (doctoral work) Target entity description: "Deep learning techniques for music recommendation (doctoral work)" is Sander Dieleman’s PhD thesis that pioneered the application of deep neural networks to improve automated music recommendation and discovery.
-
A.
Human Jukebox
Human Jukebox is the renowned marching band of Southern University, celebrated for its high-energy performances, intricate formations, and influential role in HBCU band culture.
-
B.
Deep Learning (book)
Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
-
C.
The Well-Tempered Synthesizer
The Well-Tempered Synthesizer is a pioneering 1969 electronic music album by Wendy Carlos that features Baroque and classical works performed on Moog synthesizers, helping to popularize synthesized music.
-
D.
Music Genome Project
The Music Genome Project is a comprehensive music analysis system that categorizes songs by hundreds of musical attributes to power personalized listening recommendations.
-
E.
Neural Filters
Neural Filters are Adobe Photoshop’s AI-powered tools that apply advanced, machine-learning-based adjustments and creative effects to images with minimal manual editing.
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cd03efaa748190973916bd790f6e3a |
completed | April 1, 2026, 11:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077f14804819098f443a2517ad461 |
completed | April 4, 2026, 2:31 a.m. |
| NEDg | Description generation | batch_69d07933d26c81909257a4e6a5fe1c6e |
completed | April 4, 2026, 2:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d079ed3eb48190b410934b809ebc3d |
completed | April 4, 2026, 2:39 a.m. |
Created at: March 30, 2026, 7:30 p.m.