Triple
T20407986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | What the Hell |
E500519
|
entity |
| Predicate | nextSingle |
P25313
|
FINISHED |
| Object | Smile |
—
|
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: Smile | Statement: [What the Hell, nextSingle, Smile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smile Context triple: [What the Hell, nextSingle, Smile]
-
A.
Smile
chosen
"Smile" is a 2006 pop song by British singer Lily Allen that became her breakthrough hit, known for its upbeat melody contrasted with bittersweet, vengeful lyrics.
-
B.
Smile
"Smile" is a popular country-pop song by American musician Uncle Kracker, known for its upbeat, feel-good lyrics and radio-friendly melody.
-
C.
Smile
"Smile" is a 2022 American psychological horror film about a therapist who begins experiencing terrifying, seemingly supernatural events after witnessing a patient’s bizarre suicide.
-
D.
Smile
"Smile" is a 1975 satirical comedy film that skewers the absurdities of American beauty pageants and small-town ambition.
-
E.
Smile
"Smile" is a song popularized by Michael Jackson, based on Charlie Chaplin's classic melody, known for its uplifting message about maintaining hope and positivity through hardship.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3d03ac81908f37b907ccbb5088 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.