Triple
T17360592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deadmau5 |
E422056
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Kaskade |
E1156157
|
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: Kaskade | Statement: [Deadmau5, associatedAct, Kaskade]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaskade Context triple: [Deadmau5, associatedAct, Kaskade]
-
A.
Kaskade
chosen
Kaskade is an American DJ and electronic music producer known for his melodic house tracks and influential role in the progressive and electro house scenes.
-
B.
Cascada
Cascada is a German Eurodance music group best known for their energetic dance-pop hits like "Everytime We Touch" and "Evacuate the Dancefloor."
-
C.
Art of Noise
Art of Noise is a pioneering British avant-garde synth-pop group known for its innovative use of sampling and experimental electronic production in the 1980s.
-
D.
Miike Snow
Miike Snow is a Swedish indie pop band known for its catchy, genre-blending electronic sound and hits like "Animal" and "Genghis Khan."
-
E.
Kaoma
Kaoma was a French-Brazilian band best known for their 1989 worldwide hit dance single "Lambada."
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4cacd881909fd722068b019f25 |
completed | April 19, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0195609d988190b7a70f8eabf75eaa |
completed | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:44 a.m.