Cake (2014 film)
E896922
Cake is a 2014 drama film starring Jennifer Aniston as a woman struggling with chronic pain and grief, noted for its somber tone and character-driven storytelling.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Cake (2014 film) canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T10975296 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cake (2014 film) Context triple: [Manuel Garcia-Rulfo, notableWork, Cake (2014 film)]
-
A.
Let Them Eat Cake
Let Them Eat Cake is a British historical sitcom starring Dawn French and Jennifer Saunders, set in pre-revolutionary France and known for its sharp, irreverent humor.
-
B.
Cakes (1963)
Cakes (1963) is a celebrated painting by Wayne Thiebaud that depicts an array of frosted cakes in a bright, orderly display, exemplifying his signature exploration of everyday American consumer culture through vivid color and thick impasto.
-
C.
Lots of Candles, Plenty of Cake
Lots of Candles, Plenty of Cake is a reflective memoir-essay collection by Anna Quindlen that explores aging, family, friendship, and the pleasures and challenges of middle age.
-
D.
Beecake
Beecake is a Scottish alternative rock band fronted by actor and musician Billy Boyd.
-
E.
Snow Cake
Snow Cake is a 2006 Canadian drama film starring Sigourney Weaver and Carrie-Anne Moss that explores the relationship between a reserved man and an autistic woman he meets after a tragic accident.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cake (2014 film) Target entity description: Cake is a 2014 drama film starring Jennifer Aniston as a woman struggling with chronic pain and grief, noted for its somber tone and character-driven storytelling.
-
A.
Let Them Eat Cake
Let Them Eat Cake is a British historical sitcom starring Dawn French and Jennifer Saunders, set in pre-revolutionary France and known for its sharp, irreverent humor.
-
B.
Cakes (1963)
Cakes (1963) is a celebrated painting by Wayne Thiebaud that depicts an array of frosted cakes in a bright, orderly display, exemplifying his signature exploration of everyday American consumer culture through vivid color and thick impasto.
-
C.
Lots of Candles, Plenty of Cake
Lots of Candles, Plenty of Cake is a reflective memoir-essay collection by Anna Quindlen that explores aging, family, friendship, and the pleasures and challenges of middle age.
-
D.
Beecake
Beecake is a Scottish alternative rock band fronted by actor and musician Billy Boyd.
-
E.
Snow Cake
Snow Cake is a 2006 Canadian drama film starring Sigourney Weaver and Carrie-Anne Moss that explores the relationship between a reserved man and an autistic woman he meets after a tragic accident.
- F. None of above. chosen
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
drama film
ⓘ
film ⓘ |
| characterPortrayedBy | Claire Bennett – Jennifer Aniston NERFINISHED ⓘ |
| cinematographyBy | Rachel Morrison NERFINISHED ⓘ |
| countryOfOrigin |
United States of America
ⓘ
surface form:
United States
|
| director | Daniel Barnz NERFINISHED ⓘ |
| distributor |
Cinelou Releasing
NERFINISHED
ⓘ
Freestyle Releasing NERFINISHED ⓘ |
| editedBy | Kristina Boden NERFINISHED ⓘ |
| genre | drama ⓘ |
| hasSomberTone | true ⓘ |
| mainCharacter | Claire Bennett NERFINISHED ⓘ |
| musicBy | Christophe Beck NERFINISHED ⓘ |
| narrativeFocus | character-driven storytelling ⓘ |
| nominatedFor |
Golden Globe Award for Best Actress in a Motion Picture – Drama
NERFINISHED
ⓘ
Screen Actors Guild Award for Outstanding Performance by a Female Actor in a Leading Role NERFINISHED ⓘ |
| notableFor | Jennifer Aniston dramatic performance ⓘ |
| originalLanguage | English ⓘ |
| portrays |
psychological impact of loss
ⓘ
support groups for chronic pain ⓘ |
| premiereEvent | Toronto International Film Festival NERFINISHED ⓘ |
| producer |
Ben Barnz
NERFINISHED
ⓘ
Courtney Solomon NERFINISHED ⓘ Kristin Hahn NERFINISHED ⓘ Mark Canton NERFINISHED ⓘ |
| productionCompany | Cinelou Films NERFINISHED ⓘ |
| releaseDate | 2014-09-08 ⓘ |
| runningTime | 102 minutes ⓘ |
| screenwriter | Patrick Tobin NERFINISHED ⓘ |
| setIn | Los Angeles ⓘ |
| starring |
Adriana Barraza
NERFINISHED
ⓘ
Anna Kendrick NERFINISHED ⓘ Chris Messina NERFINISHED ⓘ Felicity Huffman NERFINISHED ⓘ Jennifer Aniston NERFINISHED ⓘ Lucy Punch NERFINISHED ⓘ Mamie Gummer NERFINISHED ⓘ Sam Worthington NERFINISHED ⓘ William H. Macy NERFINISHED ⓘ |
| theatricalReleaseDate | 2015-01-23 ⓘ |
| theme |
addiction
ⓘ
chronic pain ⓘ grief ⓘ trauma ⓘ |
| yearOfWork | 2014 ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Cake (2014 film) Description of subject: Cake is a 2014 drama film starring Jennifer Aniston as a woman struggling with chronic pain and grief, noted for its somber tone and character-driven storytelling.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.