Triple
T22052854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Take a Daytrip |
E544926
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Lil Skies |
—
|
NE NERFINISHED |
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: Lil Skies | Statement: [Take a Daytrip, associatedAct, Lil Skies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lil Skies Context triple: [Take a Daytrip, associatedAct, Lil Skies]
-
A.
Lil Skies
chosen
Lil Skies is an American rapper and songwriter known for his melodic trap style and breakout hits like "Red Roses" and "Nowadays."
-
B.
Lil Star
"Lil Star" is a soulful, melodic track by Kelis featuring CeeLo Green that blends R&B and pop influences with reflective, uplifting lyrics.
-
C.
Lil Wyte
Lil Wyte is an American rapper from Memphis, Tennessee, known for his rapid-fire delivery and work with the Hypnotize Minds/Three 6 Mafia camp in the early 2000s Southern hip hop scene.
-
D.
Lil Kesh
Lil Kesh is a Nigerian rapper and singer known for his street-hop hits and prominence in the Yoruba-influenced contemporary Afrobeats scene.
-
E.
Yung Bleu
Yung Bleu is an American rapper and singer known for melodic, emotionally driven tracks like the hit single "You're Mines Still."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12855c7708190a8de44837140b654 |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:26 p.m.