Triple
T16569531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shock Value |
E402548
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Bounce |
E772034
|
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: Bounce | Statement: [Shock Value, hasPart, Bounce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bounce Context triple: [Shock Value, hasPart, 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
chosen
"Bounce" is a track from the collaborative hip-hop album "ColleGrove" by 2 Chainz and Lil Wayne.
-
D.
Bounce
Bounce is a popular brand of fabric softener dryer sheets known for reducing static cling and adding fragrance to laundry.
-
E.
Bounce
Bounce is a film whose title was later changed to "Road Show" during its production or release history.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e359580f548190a21afd148bc22d8d |
completed | April 18, 2026, 10:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ee616a0819089b3cdc1da951735 |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:16 a.m.