Triple
T6591157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy Marlow |
E159359
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Bring Your Smile Along (film)
Bring Your Smile Along is a 1955 American musical comedy film best known as the screen debut of actor-comedian Jerry Lewis.
|
E599620
|
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: Bring Your Smile Along (film) | Statement: [Lucy Marlow, notableWork, Bring Your Smile Along (film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bring Your Smile Along (film) Context triple: [Lucy Marlow, notableWork, Bring Your Smile Along (film)]
-
A.
Just Smile!
Just Smile! is the cheerful marketing slogan used by Chiquita Brands International to promote its bananas and other produce.
-
B.
Smile Away
"Smile Away" is a rock song by Paul McCartney and Wings, known for its upbeat tempo and playful lyrics.
-
C.
Smilin'
"Smilin'" is a song by Australian singer-songwriter Gideon, known for its upbeat tone and emotive, melodic pop style.
-
D.
Smile Please
"Smile Please" is a song from Stevie Wonder’s acclaimed 1974 soul and R&B album *Fulfillingness' First Finale*.
-
E.
Funny Face
Funny Face is a 1957 musical romantic comedy film starring Audrey Hepburn and Fred Astaire, celebrated for its fashion-forward Paris setting, iconic dance numbers, and classic songs.
- 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: Bring Your Smile Along (film) Triple: [Lucy Marlow, notableWork, Bring Your Smile Along (film)]
Generated description
Bring Your Smile Along is a 1955 American musical comedy film best known as the screen debut of actor-comedian Jerry Lewis.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bring Your Smile Along (film) Target entity description: Bring Your Smile Along is a 1955 American musical comedy film best known as the screen debut of actor-comedian Jerry Lewis.
-
A.
Just Smile!
Just Smile! is the cheerful marketing slogan used by Chiquita Brands International to promote its bananas and other produce.
-
B.
Smile Away
"Smile Away" is a rock song by Paul McCartney and Wings, known for its upbeat tempo and playful lyrics.
-
C.
Smilin'
"Smilin'" is a song by Australian singer-songwriter Gideon, known for its upbeat tone and emotive, melodic pop style.
-
D.
Smile Please
"Smile Please" is a song from Stevie Wonder’s acclaimed 1974 soul and R&B album *Fulfillingness' First Finale*.
-
E.
Funny Face
Funny Face is a 1957 musical romantic comedy film starring Audrey Hepburn and Fred Astaire, celebrated for its fashion-forward Paris setting, iconic dance numbers, and classic songs.
- 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_69c688366ce8819083f8883983c0df92 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6aecc969c81909a6e15ebe8dd3f94 |
completed | March 27, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbb568508190b9da3475d1620ed5 |
completed | March 27, 2026, 6:25 p.m. |
| NEDg | Description generation | batch_69c6cd08a9c88190a481d4d3f8e680bf |
completed | March 27, 2026, 6:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6cdc859cc8190bbae2efc39409021 |
completed | March 27, 2026, 6:34 p.m. |
Created at: March 27, 2026, 1:55 p.m.