Triple
T2416298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miguel Jontel Pimentel |
E52310
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | How Many Drinks? |
E49775
|
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: How Many Drinks? | Statement: [Miguel Jontel Pimentel, notableWork, How Many Drinks?]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: How Many Drinks? Context triple: [Miguel Jontel Pimentel, notableWork, How Many Drinks?]
-
A.
How Many Drinks?
chosen
"How Many Drinks?" is an R&B song by American singer Miguel, known for its smooth vocals and lyrics about seduction and nightlife, released from his 2012 album *Kaleidoscope Dream*.
-
B.
Drink a Beer
"Drink a Beer" is a reflective country ballad by Luke Bryan that poignantly addresses loss and remembrance.
-
C.
Cocktail Time
"Cocktail Time" is a comic novel by P. G. Wodehouse featuring the mischievous Earl of Ickenham (Uncle Fred) as he orchestrates romantic entanglements and social chaos in his characteristic lighthearted style.
-
D.
Brad's Drink
Brad's Drink was the original name of the soft drink that later became known worldwide as Pepsi.
-
E.
Hold My Liquor
"Hold My Liquor" is a moody, atmospheric hip-hop track by Kanye West featuring introspective lyrics and experimental 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94d048481908409d60129aef747 |
completed | March 7, 2026, 6:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf4a784c819082c47e3936242478 |
completed | March 9, 2026, 12:38 p.m. |
Created at: March 6, 2026, 9:42 p.m.