Triple
T13042373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Party Rock |
E327225
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Get Crazy |
E620322
|
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: Get Crazy | Statement: [Party Rock, hasTrack, Get Crazy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Get Crazy Context triple: [Party Rock, hasTrack, Get Crazy]
-
A.
Get Crazy
chosen
Get Crazy is a 1983 rock-and-roll comedy film centered on a chaotic New Year's Eve concert at a fictional music venue.
-
B.
Go Crazy
"Go Crazy" is a popular hip-hop single by Young Thug, known for its catchy melody and energetic production.
-
C.
Go Crazy
"Go Crazy" is a popular hip-hop single by Jeezy featuring Jay-Z, known for its soulful production and influential role in mid-2000s Southern rap.
-
D.
Get Happy
"Get Happy" is a classic upbeat song closely associated with Judy Garland, celebrated for its joyful gospel-inflected style and iconic performance in the film "Summer Stock."
-
E.
Get Em
"Get Em" is a track from Lil Wayne’s mixtape *Dedication 2*, showcasing his rapid-fire wordplay and punchline-heavy Southern rap style.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804f0318819081516e2ca1de6797 |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd5139c8190aaec6487f074f251 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:56 p.m.