Triple
T13982736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace |
E336354
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Smile
"Smile" is a song by American singer Grace, known for its soulful pop style and emotive vocals.
|
E1072424
|
NE FINISHED |
How this triple was built (4 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: [Grace, hasTrack, Smile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smile Context triple: [Grace, hasTrack, Smile]
-
A.
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.
-
B.
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.
-
C.
Smile
"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.
-
D.
Smile
"Smile" is a popular country-pop song by American musician Uncle Kracker, known for its upbeat, feel-good lyrics and radio-friendly melody.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Smile Triple: [Grace, hasTrack, Smile]
Generated description
"Smile" is a song by American singer Grace, known for its soulful pop style and emotive vocals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Smile Target entity description: "Smile" is a song by American singer Grace, known for its soulful pop style and emotive vocals.
-
A.
Smile
"Smile" is a popular country-pop song by American musician Uncle Kracker, known for its upbeat, feel-good lyrics and radio-friendly melody.
-
B.
Smile
"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.
-
C.
Smile
"Smile" is a song featured on Mary J. Blige's R&B album "Strength of a Woman."
-
D.
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.
-
E.
Smile
"Smile" is a smooth, romantic Afrobeats track by Nigerian artist Wizkid featuring H.E.R., known for its mellow vibe and themes of love and gratitude.
- F. None of above. chosen
Provenance (5 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea2e8808190a1203a6386224bd8 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1e5f2008190a0701ae37ed5219d |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba785e17c819081d09f7891914665 |
completed | May 6, 2026, 8:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba82ca04c8190863932895fa8212a |
completed | May 6, 2026, 8:44 p.m. |
Created at: April 9, 2026, 10:18 p.m.