Triple
T18831099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Hour |
E460529
|
entity |
| Predicate | hasSingle |
P3282
|
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: [Happy Hour, hasSingle, Smile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smile Context triple: [Happy Hour, hasSingle, Smile]
-
A.
Smile
chosen
"Smile" is a 2020 pop album by American singer Katy Perry that explores themes of resilience, self-acceptance, and personal growth.
-
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 song featured on the album *The Art of Elegance*, known for its smooth, classic vocal style and refined, jazz-influenced arrangement.
-
D.
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.
-
E.
Smile
"Smile" is a 1975 satirical comedy film that skewers the absurdities of American beauty pageants and small-town ambition.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a9992bb081908ba517a5c9d93ef3 |
completed | April 20, 2026, 4:20 a.m. |
Created at: April 10, 2026, 11:56 a.m.