Triple
T17439488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anything Goes |
E424109
|
entity |
| Predicate | single |
P3283
|
FINISHED |
| Object | Sun Daze |
—
|
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: Sun Daze | Statement: [Anything Goes, single, Sun Daze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sun Daze Context triple: [Anything Goes, single, Sun Daze]
-
A.
Sun Daze
chosen
"Sun Daze" is a 2014 country-pop party anthem by Florida Georgia Line known for its laid-back, beachy vibe and playful, carefree lyrics.
-
B.
Sunshine Daydream
Sunshine Daydream is the exuberant, improvisational coda often attached to live performances of the Grateful Dead song "Sugar Magnolia," known for its extended jams and climactic energy.
-
C.
Soak Up the Sun
"Soak Up the Sun" is a 2002 pop-rock song by Sheryl Crow known for its upbeat, feel-good sound and themes of optimism and enjoying life's simple pleasures.
-
D.
Sunny Days
"Sunny Days" is a song by the musical group Arm in Arm.
-
E.
Sunny Day
Sunny Day is an animated children's television series about a talented young hairstylist and problem-solver who runs a salon in the colorful town of Friendly Falls.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff63e5481908a3ea0aa221360c5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 5:46 a.m.