Triple
T13576636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dean Zanuck |
E324302
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Get Low |
E1008444
|
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 Low | Statement: [Dean Zanuck, notableWork, Get Low]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Get Low Context triple: [Dean Zanuck, notableWork, Get Low]
-
A.
Get Low
chosen
Get Low is a 2009 independent drama film set in the 1930s American South, following a reclusive hermit who plans his own funeral party while still alive.
-
B.
Get Low
"Get Low" is a 2002 crunk anthem by Lil Jon & the East Side Boyz featuring the Ying Yang Twins that became a major club hit and a defining track of early-2000s Southern hip hop.
-
C.
How Low
"How Low" is a popular hip-hop single by American rapper Ludacris, known for its catchy hook and heavy club-oriented production.
-
D.
“Get Low, Get High”
“Get Low, Get High” is a country-rap song by American artist Willie Jones that blends hip-hop beats with country storytelling and party themes.
-
E.
So Low
"So Low" is a song by American rapper Talib Kweli from his album *Gutter Rainbows*, showcasing his socially conscious lyricism over soulful, boom-bap-influenced production.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02de1988190af2d473973ecd529 |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bbbe3c08190a359dfe7c3c8f15c |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.