11.22.63 (TV miniseries)
E819974
11.22.63 is a science fiction thriller TV miniseries based on Stephen King’s novel, following a man who travels back in time to try to prevent the assassination of John F. Kennedy.
All labels observed (1)
| Label | Occurrences |
|---|---|
| 11.22.63 (TV miniseries) canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9767962 — 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: 11.22.63 (TV miniseries) Context triple: [Alex Heffes, composedMusicFor, 11.22.63 (TV miniseries)]
-
A.
Der Kabelkanal
Der Kabelkanal was the original name of the German television channel that later became known as ProSieben.
-
B.
From Scratch (TV miniseries)
From Scratch is a romantic drama miniseries about an American woman who finds love and family in Italy, adapted from Tembi Locke’s memoir and featuring Anika Noni Rose in a supporting role.
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C.
112 (album)
112 is the self-titled debut studio album by American R&B group 112, known for its smooth harmonies and hit singles that helped define late-1990s R&B.
-
D.
Twelve Months, Eleven Days
"Twelve Months, Eleven Days" is a pop album by British singer-songwriter Gary Barlow, known for its melodic ballads and reflective lyrics following his success with Take That.
-
E.
The Kill Point (TV miniseries)
The Kill Point is an American crime drama TV miniseries that follows a tense hostage standoff after a botched bank robbery carried out by a group of Iraq War veterans.
- 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: 11.22.63 (TV miniseries) Target entity description: 11.22.63 is a science fiction thriller TV miniseries based on Stephen King’s novel, following a man who travels back in time to try to prevent the assassination of John F. Kennedy.
-
A.
Der Kabelkanal
Der Kabelkanal was the original name of the German television channel that later became known as ProSieben.
-
B.
From Scratch (TV miniseries)
From Scratch is a romantic drama miniseries about an American woman who finds love and family in Italy, adapted from Tembi Locke’s memoir and featuring Anika Noni Rose in a supporting role.
-
C.
112 (album)
112 is the self-titled debut studio album by American R&B group 112, known for its smooth harmonies and hit singles that helped define late-1990s R&B.
-
D.
Twelve Months, Eleven Days
"Twelve Months, Eleven Days" is a pop album by British singer-songwriter Gary Barlow, known for its melodic ballads and reflective lyrics following his success with Take That.
-
E.
The Kill Point (TV miniseries)
The Kill Point is an American crime drama TV miniseries that follows a tense hostage standoff after a botched bank robbery carried out by a group of Iraq War veterans.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf | television miniseries ⓘ |
| adaptationOfGenre | time-travel novel ⓘ |
| alsoKnownAs | 11.22.63: Event Date ⓘ |
| audioFormat | 5.1 surround sound ⓘ |
| basedOn | 11/22/63 (novel) NERFINISHED ⓘ |
| basedOnWorkBy | Stephen King NERFINISHED ⓘ |
| character |
Bill Turcotte
NERFINISHED
ⓘ
Jake Epping NERFINISHED ⓘ Lee Harvey Oswald NERFINISHED ⓘ Sadie Dunhill NERFINISHED ⓘ |
| composer | Alex Heffes NERFINISHED ⓘ |
| countryOfOrigin |
United States of America
ⓘ
surface form:
United States
|
| developedForTelevisionBy | Bridget Carpenter NERFINISHED ⓘ |
| distributor | Hulu NERFINISHED ⓘ |
| executiveProducer |
Bad Robot Productions
NERFINISHED
ⓘ
Bridget Carpenter NERFINISHED ⓘ Bryan Burk NERFINISHED ⓘ J. J. Abrams NERFINISHED ⓘ Stephen King NERFINISHED ⓘ |
| genre |
drama
ⓘ
science fiction ⓘ thriller ⓘ |
| hasFormat | limited series ⓘ |
| languageOfWorkOrName | English ⓘ |
| mainSubject |
assassination of John F. Kennedy
NERFINISHED
ⓘ
time travel ⓘ |
| narrativeFocus | preventing a historical assassination ⓘ |
| numberOfEpisodes | 8 ⓘ |
| numberOfSeasons | 1 ⓘ |
| originalLanguage | English ⓘ |
| originalNetwork | Hulu NERFINISHED ⓘ |
| originalReleaseEndDate | 2016-04-04 ⓘ |
| originalReleaseStartDate | 2016-02-15 ⓘ |
| pictureFormat | HDTV ⓘ |
| productionCompany |
Bad Robot Productions
NERFINISHED
ⓘ
Warner Bros. Television ⓘ |
| releasePlatform | streaming television ⓘ |
| settingLocation |
Dallas, Texas
NERFINISHED
ⓘ
Maine NERFINISHED ⓘ |
| settingTimePeriod | 1960s ⓘ |
| starring |
Chris Cooper
NERFINISHED
ⓘ
Daniel Webber NERFINISHED ⓘ George MacKay NERFINISHED ⓘ James Franco NERFINISHED ⓘ Lucy Fry NERFINISHED ⓘ Sarah Gadon NERFINISHED ⓘ |
| title | 11.22.63 NERFINISHED ⓘ |
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: 11.22.63 (TV miniseries) Description of subject: 11.22.63 is a science fiction thriller TV miniseries based on Stephen King’s novel, following a man who travels back in time to try to prevent the assassination of John F. Kennedy.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.