Triple
T8425451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSTRKRFT |
E198972
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Bounce
"Bounce" is a popular electro house track by Canadian electronic music duo MSTRKRFT, known for its heavy synths and club-oriented energy.
|
E733232
|
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: Bounce | Statement: [MSTRKRFT, notableSong, Bounce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bounce Context triple: [MSTRKRFT, notableSong, Bounce]
-
A.
Bounce
"Bounce" is a 2002 hard rock album by Bon Jovi that reflects themes of resilience and renewal, influenced in part by the aftermath of the September 11 attacks.
-
B.
Bounce
"Bounce" is a popular Afrobeats song by Nigerian singer Rema, known for its energetic production and catchy, dance-oriented style.
-
C.
Bounce (album)
Bounce is a jazz album by acclaimed trumpeter and composer Terence Blanchard that showcases his modern, post-bop style and rich, cinematic arrangements.
-
D.
Rebound
Rebound is a 2005 sports comedy film starring Martin Lawrence as a disgraced college basketball coach who must redeem himself by leading a misfit middle school team.
-
E.
Bounce Back
"Bounce Back" is a 2016 hit single by American rapper Big Sean known for its motivational theme about recovering from setbacks and its strong commercial success.
- 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: Bounce Triple: [MSTRKRFT, notableSong, Bounce]
Generated description
"Bounce" is a popular electro house track by Canadian electronic music duo MSTRKRFT, known for its heavy synths and club-oriented energy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bounce Target entity description: "Bounce" is a popular electro house track by Canadian electronic music duo MSTRKRFT, known for its heavy synths and club-oriented energy.
-
A.
Bounce
"Bounce" is a 2002 hard rock album by Bon Jovi that reflects themes of resilience and renewal, influenced in part by the aftermath of the September 11 attacks.
-
B.
Bounce
"Bounce" is a popular Afrobeats song by Nigerian singer Rema, known for its energetic production and catchy, dance-oriented style.
-
C.
Bounce (album)
Bounce is a jazz album by acclaimed trumpeter and composer Terence Blanchard that showcases his modern, post-bop style and rich, cinematic arrangements.
-
D.
Rebound
Rebound is a 2005 sports comedy film starring Martin Lawrence as a disgraced college basketball coach who must redeem himself by leading a misfit middle school team.
-
E.
Bounce Back
"Bounce Back" is a 2016 hit single by American rapper Big Sean known for its motivational theme about recovering from setbacks and its strong commercial success.
- 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb85a2871081908a4093838fc93b5a |
completed | March 31, 2026, 8:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0364f294819091ef9f39429f3fb5 |
completed | April 2, 2026, 5:49 a.m. |
| NEDg | Description generation | batch_69ce07837648819080cd4026af55b246 |
completed | April 2, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce083cee848190b27a7dd19a16a0dc |
completed | April 2, 2026, 6:10 a.m. |
Created at: March 30, 2026, 6:07 p.m.