Triple
T6509164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amplified |
E150083
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Go Hard |
E581475
|
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: Go Hard | Statement: [Amplified, hasPart, Go Hard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Go Hard Context triple: [Amplified, hasPart, Go Hard]
-
A.
Hustle Harder
"Hustle Harder" is a hip-hop track by Common from his album "Nobody's Smiling," reflecting themes of perseverance and street struggle.
-
B.
Get Hard
Get Hard is a 2015 American comedy film starring Will Ferrell and Kevin Hart, centered on a wealthy businessman preparing for prison with the help of a small-time car washer.
-
C.
We Go Hard
"We Go Hard" is a hip-hop track by DMX featured on his album "Year of the Dog... Again."
-
D.
"Go Hard"
chosen
"Go Hard" is a track from Lil Wayne’s 2002 studio album *500 Degreez*, showcasing his early Southern hip hop style.
-
E.
Gotta Have It
"Gotta Have It" is a high-energy hip hop track by Jay-Z and Kanye West from their collaborative album *Watch the Throne*, known for its dense sampling and rapid-fire back-and-forth verses.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f386aa08190bfc8592a92ec6339 |
completed | March 27, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb5782fc8190a56b714bbc007490 |
completed | March 27, 2026, 6:24 p.m. |
Created at: March 27, 2026, 1:43 p.m.