Triple
T8507034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bounce Back |
E201359
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Hitmaka |
E704717
|
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: Hitmaka | Statement: [Bounce Back, producer, Hitmaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hitmaka Context triple: [Bounce Back, producer, Hitmaka]
-
A.
Hitmaka
chosen
Hitmaka is an American record producer, songwriter, and former rapper known for crafting numerous contemporary hip-hop and R&B hits for major artists.
-
B.
Loona
Loona is a celebrated Punjabi epic verse play by Shiv Kumar Batalvi that reimagines the traditional legend of Puran Bhagat from the perspective of the vilified stepmother, Loona.
-
C.
Nine Muses
The Nine Muses are the goddesses of inspiration in Greek mythology, each presiding over a different art or science such as epic poetry, history, music, and dance.
-
D.
Arashi
Arashi is a popular Japanese boy band formed under Johnny & Associates, known for their chart-topping J-pop hits, television appearances, and widespread influence in Japanese entertainment.
-
E.
Nogizaka
Nogizaka is a district in Tokyo, Japan, known for its upscale urban atmosphere and proximity to cultural landmarks and institutions.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5de18448190a695eec609b34e1a |
completed | March 31, 2026, 3:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d257a748190b33873ee0d252d2e |
completed | April 2, 2026, 1:20 p.m. |
Created at: March 30, 2026, 6:14 p.m.