PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q28865 wdt:P31 wd:Q899523 .
  wd:Q899523 wdt:P279 * wd:Q9143
}

True

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Is Python a kind of Programming languages?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
Which airports does Yeti Airlines serve?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1480118 wdt:P113 ?uri .
}

Using entities:
Yeti Airlines, also known as Yeti Airlines Domestic Pvt. Ltd. (wd:Q1480118): Airline based in Kathmandu, Nepal.

Using properties:
airline hub, also known as hub airport, hub (wd:P113 as wdt): airport that serves as a hub for an airline

Example 2:
Question:
Give me all cars that are produced in Germany.

SPARQL:
SELECT DISTINCT * WHERE {
  ?s1 wdt:P31 wd:Q59773381 .
  ?s1 wdt:P176 ?o1 .
  ?o1 wdt:P17 wd:Q183 .
  ?o1 wdt:P31 wd:Q786820 .
}

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
automobile model series, also known as car model line, car series, car model series, car line, automobile series (wd:Q59773381): group of related automobile models
automobile manufacturer, also known as auto manufacturer, car manufacturer, car maker, car builder, automotive company (wd:Q786820): company that makes automobiles

Using properties:
manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as wdt): (main or final) manufacturer or producer of this product
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
Who wrote the song Hotel California?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q780394 wdt:P86 ?uri
}

Using entities:
Hotel California (wd:Q780394): song written and composed by Don Felder, Don Henley and Glenn Frey; originally recorded by Eagles and released 1976

Using properties:
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

[Assistant]
From the examples, we can see how to structure a basic SPARQL query to check if one entity is a specific type of another entity. In our case, we want to check if Python (the programming language) is a kind of programming language. We need to identify the entity for Python and the entity for programming languages, and then use the `wdt:P31` property to check if Python is an instance of a programming language.

First, let's search for the entity representing Python (the programming language).

[Tool]
Top 10 entity alternatives:
1. Python, also known as Python (software), Python (scripting language), Python Programming Language, Python (Programming Language), Python (computer language) (wd:Q28865): general-purpose programming language
2. Python: The future programming language (wd:Q113194464): scientific article published on 20 January 2022
3. Efficiency asynchronous application programming language Python (wd:Q113231212): scientific article published on 18 December 2018
4. PYTHON: THE MOST ADVANCED PROGRAMMING LANGUAGE (wd:Q120764715): scientific article published in 2022
5. Python as Multi Paradigm Programming Language (wd:Q113199030): scientific article published on 16 January 2020
6. Type inference for Python programming language (wd:Q113263977): scientific article published on 25 November 2014
7. Application of python programming language in measurements (wd:Q113222154): scientific article published on 08 February 2019
8. On the Python programming language for statisticians (wd:Q113229894): scientific article published on 29 April 2020
9. TEACHING ALGORITHMIZATION AND PROGRAMMING USING PYTHON LANGUAGE (wd:Q113264868): scientific article published on 17 June 2015
10. Desktop Based Personal Assistance Using Python Programming Language (wd:Q120776424): scientific article published in 2023

[Assistant] The top result for "Python programming language" is `wd:Q28865`, which represents the general-purpose programming language Python. Next, let's search for the entity representing "programming language."

[Tool]
Top 10 entity alternatives:
1. programming language, also known as coding language, computer language, computer programming, computer programming language (wd:Q9143): language for communicating instructions to a machine
2. language-oriented programming language (wd:Q28923009): programming language
3. programming language (wd:L475355-S2)
4. programming language (wd:L501100-S3)
5. programming language (wd:L546252-S1)
6. programming language (wd:L546252-S2)
7. programming language (wd:L551138-S1)
8. programming language (wd:L434060-S1)
9. programming language (wd:L254536-S2)
10. programming language (wd:L315901-S1)

[Assistant]
The top result for "programming language" is `wd:Q9143`, which represents the concept of a programming language. Now, we can construct a SPARQL query to check if Python (the programming language) is an instance of a programming language.

We will use the `wdt:P31` property to check if Python (`wd:Q28865`) is an instance of a programming language (`wd:Q9143`).

Let's write and execute the SPARQL query.

[Tool] False

[Assistant]
The SPARQL query returned `False`, indicating that Python (the programming language) is not directly classified as an instance of a programming language in Wikidata. However, this might be due to the way the data is structured in Wikidata. Let's verify if Python is a subclass of a programming language or if it has a more specific classification.

We can check if Python is a subclass of a programming language by using the `wdt:P279` property, which represents the "subclass of" relationship.

Let's write and execute this SPARQL query.

[Tool] False

[Assistant]
The SPARQL query using the `wdt:P279*` property (which checks for transitive subclass relationships) also returned `False`. This indicates that Python (the programming language) is not directly classified as a subclass of a programming language in Wikidata.

However, it is generally accepted that Python is a programming language. The issue here might be with the specific way the data is structured in Wikidata. To provide a more accurate answer, we can look at the direct properties and statements associated with Python to see if it is indeed classified as a programming language in any way.

Let's list the triples for Python to see if there are any relevant properties or statements.

[Tool]
Got 1,169 rows and 3 columns, showing the first 10 rows below:
| subject            | property                                       | object                                                                                |
| ------------------ | ---------------------------------------------- | ---------------------------------------------------------------------------------------------- |
| Python (wd:Q28865) | instance of (wdt:P31)                          | object-based language (wd:Q899523)                                                             |
| Python (wd:Q28865) | Commons category (wdt:P373)                    | Python (programming language)                                                                  |
| Python (wd:Q28865) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/CPT-TheoryOfComp-Binary-Search-Python.png> |
| Python (wd:Q28865) | copyright status (wdt:P6216)                   | copyrighted (wd:Q50423863)                                                                     |
| Python (wd:Q28865) | inception (wdt:P571)                           | 1991-02-20T00:00:00Z (xsd:dateTime)                                                            |
| Python (wd:Q28865) | described at URL (wdt:P973)                    | <https://marketplace.sshopencloud.eu/tool-or-service/tt0gGA>                                   |
| Python (wd:Q28865) | has part(s) (wdt:P527)                         | integrated development environment (wd:Q13741)                                                 |
| Python (wd:Q28865) | copyright license (wdt:P275)                   | Python Software Foundation License (wd:Q2600299)                                               |
| Python (wd:Q28865) | official website (wdt:P856)                    | <https://www.python.org/>                                                                      |
| Python (wd:Q28865) | on focus list of Wikimedia project (wdt:P5008) | wd:Q6173448                                                                                |
| ...                | ...                                            | ...                                                                                |

[Assistant]
From the triples listed for Python (the programming language), we can see that it is classified as an "object-based language" (`wd:Q899523`). However, this does not directly confirm that Python is a programming language.

To further investigate, let's check if "object-based language" is a subclass of "programming language".

[Tool] True

[Assistant]
The SPARQL query returned `True`, indicating that "object-based language" (`wd:Q899523`) is a subclass of "programming language" (`wd:Q9143`). Since Python is classified as an "object-based language," this confirms that Python is indeed a kind of programming language.

Therefore, the answer to the question "Is Python a kind of Programming languages?" is `True`.

Let's finalize the answer with the appropriate SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly checks if Python (wd:Q28865) is an instance of a programming language (wd:Q9143) through the intermediate class of object-based languages (wd:Q899523). The result is true, which means Python is indeed a kind of programming language. The query follows all the rules and is well-constructed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q5287 wdt:P1098 ?numberOfSpeakers .
  FILTER ( ?numberOfSpeakers > 100000000 )
}

True

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Do more than 100000000 people speak Japanese?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
Where is the residence of the prime minister of Spain?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q844587 wdt:P263 ?uri
}

Using entities:
Prime Minister of Spain, also known as president of the Government of Spain (wd:Q844587): head of government of Spain

Using properties:
official residence, also known as resides at, lives in, palace, presidential mansion, presidential palace (wd:P263 as wdt): the residence at which heads of government and other senior figures officially reside, residence

Example 2:
Question:
Give me the websites of companies with more than 500000 employees.

SPARQL:
SELECT DISTINCT ?string WHERE {
  ?uri wdt:P31 / ( wdt:P279 * ) wd:Q4830453 .
  ?uri wdt:P1128 ?number .
  FILTER ( ?number > 500000 ) .
  ?uri wdt:P856 ?string .
}

Using entities:
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

Using properties:
employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as wdt): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL

Example 3:
Question:
Which films starring Clint Eastwood did he direct himself?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P57 wd:Q43203 ; wdt:P161 wd:Q43203 .
}

Using entities:
Clint Eastwood, also known as Clinton Eastwood Jr., Clinton Eastwood, Jr., Clinton "Clint" Eastwood, Jr., Clinton Eastwood (wd:Q43203): American actor and film director (born 1930), film score composer, television actor, film producer, film director, restaurateur, screenwriter, film actor, songwriter, activist, composer, director, singer, writer, mayor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

[Assistant] Based on the examples, we need to find the number of speakers of the Japanese language. Let's first identify the entity for the Japanese language.

[Tool]
Top 10 entity alternatives:
1. Japanese, also known as Japanese language, Japanesic (wd:Q5287): language spoken in East Asia
2. Japanese language (wd:Q10855582): school subject
3. Japanese Language (wd:Q110262521): Stack Exchange site for students, teachers, and linguists wanting to discuss the finer points of the Japanese language
4. Japanese (language) (wd:L612945-S1)
5. Japanese Wikipedia, also known as ja.wikipedia.org, jpwp, Jp.wikipedia.org, JAWP, jawp (wd:Q177837): Japanese-language edition of Wikipedia
6. Japanese Sign Language, also known as JSL (wd:Q35601): sign language
7. Classical Japanese, also known as Classical Japanese language (wd:Q1332057): literary form of the Japanese language, standard until WW2, based on Heian-period Early Middle Japanese with later influences
8. Japanese language education, also known as teaching Japanese as a foreign language (wd:Q17214937)
9. dictionary of the Japanese language, also known as dictionary of Japanese, Japanese language dictionary, Japanese dictionary (wd:Q6158568): language version of dictionary
10. Japanese language department (wd:Q11086620)

[Assistant] The correct entity for the Japanese language is wd:Q5287. Now, let's find the property that represents the number of speakers of a language.

[Tool]
Top 10 property alternatives:
1. number of speakers, writers, or signers, also known as signers of a language, speakers of language, writers of a language (wd:P1098 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of people who use a language
2. number of viewers/listeners, also known as plays, watches, watch count, views, view number (wd:P5436 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of viewers of a television or broadcasting program; web traffic on websites
3. number of words, also known as word count, words (number of) (wd:P6570 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of words in text
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): language designated as official by this item, language used
5. speaker, also known as speech by, spoken by (wd:P823 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): person who is speaker for this event, ceremony, keynote, presentation or in a literary work, participant, spoken by
6. spoken by, also known as speaker (wd:P10894 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the person who is speaking in this audio or video file
7. number of aid beneficiaries, also known as number of aid recipients, number of beneficiaries, number of people reached, people reached (wd:P9077 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of people reached with international aid programmes, acti...ctivities. Qualify with "point in time" (P585) where appropriate
8. intended public, also known as for, user group, target market, target group, target demographic (wd:P2360 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): this work, product, object or event is intended for, or has been designed to that person or group of people, animals, plants, etc
9. number of registered users/contributors, also known as number of contributors, number of registered users, number of users, users (wd:P1833 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of registered users on a website
10. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): number of entities that are part of an organization at a particular time

[Assistant]
The correct property for the number of speakers of a language is wd:P1098. Now, let's construct a SPARQL query to check if more than 100,000,000 people speak Japanese.

We will use an ASK query to get a boolean response.

```sparql
ASK WHERE {
  wd:Q5287 wdt:P1098 ?numberOfSpeakers .
  FILTER (?numberOfSpeakers > 100000000)
}
```

Let's execute this query.

[Tool] True

[Assistant]
The SPARQL query confirms that more than 100,000,000 people speak Japanese.

Here is the final SPARQL query and the answer:

```sparql
ASK WHERE {
  wd:Q5287 wdt:P1098 ?numberOfSpeakers .
  FILTER (?numberOfSpeakers > 100000000)
}
```

Answer: True

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correctly formulated as an ASK query and it accurately checks if the number of speakers of Japanese is greater than 100,000,000. The answer provided is correct based on the execution result.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?castMember ?birthDate WHERE {
  wd:Q48817408 wdt:P161 ?castMember .
  ?castMember wdt:P569 ?birthDate .
}
ORDER BY ?birthDate
LIMIT 1

The oldest cast member of the Netflix show 'Queer Eye' is Karamo Brown.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Who is the oldest cast member of the Netflix show “Queer Eye” ?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
Who was called Rodzilla?

SPARQL:
SELECT * WHERE {
  ?uri skos:altLabel "Rodzilla" @en .
}

Example 2:
Question:
Who was the wife of U.S. president Lincoln?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q91 wdt:P26 ?uri .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

Example 3:
Question:
Which building after the Burj Khalifa has the most floors?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q12495 wdt:P1101 ?bkFloors .
  ?uri wdt:P1101 ?otherFloors .
  FILTER ( ?otherFloors > ?bkFloors )
}
ORDER BY ?otherFloors
LIMIT 1

Using entities:
Burj Khalifa, also known as 1 Sheikh Mohammed bin Rashid Boulevard, Burj Dubai, Khalifa Tower (wd:Q12495): skyscraper in Dubai, United Arab Emirates

Using properties:
floors above ground, also known as floor count, stories, storeys, number of floors, levels above ground (wd:P1101 as wdt): above ground floor count of a building (ground floor and attic included)

[Assistant] Based on the examples, we need to identify the cast members of the Netflix show "Queer Eye" and then determine who among them is the oldest. Let's first find the entity for the show "Queer Eye".

[Tool]
Top 10 entity alternatives:
1. Queer Eye, also known as Queer Eye for the Straight Guy (wd:Q1418248): 2003 American reality television series
2. Queer Eye (wd:Q48817408): 2018 American television series
3. Queer Eye: Germany, also known as Queer Eye Germany (wd:Q111914878): German reality television series
4. Queer Eye, season 4 (wd:Q67649081): season of television series
5. Queer Eye, season 3 (wd:Q65590894): season of television series
6. Queer Eye, season 2 (wd:Q57313933): season of television series
7. Queer Eye, season 1 (wd:Q57312338): season of television series
8. Queer Eye, season 5 (wd:Q97455984): 5th season of Netflix series
9. Queer Eye, season 6 (wd:Q110791710): 6th season of Netflix series
10. Queer Eyes, Full Hearts (wd:Q18636591): episode of Modern Family

[Assistant] The correct entity for the Netflix show "Queer Eye" is `wd:Q48817408`. Now, let's find the cast members of this show.

[Tool]
Top 10 property alternatives:
1. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
3. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
4. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as wdt/p): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
5. narrative location, also known as set in location, set in, setting, setting location, setting of work (wd:P840 as wdt/p): the narrative of the work is set in this location, significant place, depicts
6. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
7. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
8. distribution format, also known as book format, type of media, publication format, method of distribution, medium (wd:P437 as wdt/p): method (or type) of distribution for the subject
9. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as wdt/p): name of the Reddit forum associated to this subject
10. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as wdt/p): network(s) or service(s) that originally broadcast a radio or television program, broadcast by

No other items found

[Assistant] The property `cast member` (P161) seems to be the right choice for finding the cast members of the show. Let's use this property to list the cast members of "Queer Eye" (wd:Q48817408).

[Tool]
Got 6 rows and 1 column:
| castMember                       |
| -------------------------------- |
| Jeremiah Brent (wd:Q29452671)    |
| Karamo Brown (wd:Q44870529)      |
| Bobby Berk (wd:Q49729241)        |
| Antoni Porowski (wd:Q50377216)   |
| Jonathan Van Ness (wd:Q50379405) |
| Tan France (wd:Q50379407)        |

[Assistant]
We have identified the cast members of the Netflix show "Queer Eye". Now, we need to determine who among these cast members is the oldest. To do this, we will need to find the birth dates of these individuals and compare them.

First, let's find the birth date property for these entities.

[Tool]
Top 10 property alternatives:
1. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): date on which the subject was born, inception
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): most specific known birth location of a person, animal or fictional character, location
3. birthday, also known as b-day, bday, birth day (wd:P3150 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the object is a country that recognizes the subject as its citizen, country
5. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): what the place, monument, memorial, or holiday, commemorates, main subject
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): full name of a person at birth, if different from their current, generally used name, name
7. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): dissolved, abolished or demolished date, date on which the subject died, end time
8. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): time when an entity begins to exist; for date of official opening use P1619, start time
9. website username or ID, also known as user name, website username, website ID, username in social media, username (wd:P554 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): username or identifier on a website that the person or movement ... account on, for use as qualifier of "website account on" (P553)
10. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): alias used by someone (for nickname use P1449), name

[Assistant] The property `date of birth` (P569) is the correct one for finding the birth dates of the cast members. Let's retrieve the birth dates for each of the cast members and then determine who is the oldest.

[Tool]
Got 1 row and 2 columns:
| castMember                  | birthDate                           |
| --------------------------- | ----------------------------------- |
| Karamo Brown (wd:Q44870529) | 1980-11-02T00:00:00Z (xsd:dateTime) |

[Assistant]
The oldest cast member of the Netflix show "Queer Eye" is Karamo Brown, born on November 2, 1980.

Let's finalize the answer with the SPARQL query and the result.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies Karamo Brown as the oldest cast member of the Netflix show 'Queer Eye' based on the birth dates of the cast members.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?date WHERE {
  wd:Q220015 wdt:P571 ?date .
}

January 1, 1968

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] when was the magazine in which hunter x hunter is published established?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
Give me all cosmonauts.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q11631 .
  {
    ?uri wdt:P27 wd:Q15180
  } UNION {
    ?uri wdt:P27 wd:Q159
  }
}

Using entities:
astronaut, also known as cosmonaut, vyomanaut, taikonaut, spationaut, spacionaut (wd:Q11631): person who commands, pilots, or serves as a crew member of a spacecraft
Soviet Union, also known as Union of Soviet Socialist Republics, The USSR, URS, the Union of Soviet Socialist Republics, the Soviet Union (wd:Q15180): former country in Eurasia (1922–1991)
Russia, also known as Russian Federation, RUS, RU, RF, ISO 3166-1:RU (wd:Q159): country in Eastern Europe and Northern Asia

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt): the object is a country that recognizes the subject as its citizen, country

Example 2:
Question:
Give me the birth place of Frank Sinatra.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q40912 wdt:P19 ?uri
}

Using entities:
Frank Sinatra, also known as Old Blue Eyes, Ol' Blue Eyes, Sinatra, Francis Albert Sinatra (wd:Q40912): American singer and actor (1915–1998), television actor, film producer, film director, voice actor, film actor, director, producer, singer, actor

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 3:
Question:
What is the time zone of Salt Lake City?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q23337 wdt:P421 ?o1 .
}

Using entities:
Salt Lake City, also known as Salt Lake, Salt Lake City, UT, Salt Lake City, Utah, SLC (wd:Q23337): city in and county seat of Salt Lake County, Utah, United States and the capital of Utah

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant] Based on the examples, we need to identify the magazine where Hunter x Hunter is published and then find when it was established. Let's first search for the entity "Hunter x Hunter".

[Tool]
Top 10 entity alternatives:
1. Hunter × Hunter, also known as HUNTER × HUNTER, Hunter x Hunter, HXH (wd:Q696071): Japanese manga series
2. Hunter × Hunter, also known as H×H, Hunter x Hunter, HxH (wd:Q70209136): 2011 Japanese anime television series
3. Hunter × Hunter, also known as Hunter x Hunter, HxH (wd:Q21232458): 1999 Japanese anime television series
4. Monster Hunter Generations, also known as Monster Hunter X (wd:Q20856979): 2015 Japanese video game
5. Hunter Xcite (wd:Q60767092): sailboat class
6. Xavier Hunter (wd:Q100806788): basketball player
7. Hunter × Hunter: Phantom Rouge, also known as Hunter X Hunter: Phantom Rouge (wd:Q11398237): 2013 film by Yūzō Satō
8. City Hunter XYZ (wd:Q97170832): fan film by Filip Wong
9. Monster Hunter Generations Ultimate, also known as Monster Hunter XX (wd:Q30302563): 2017 video game
10. XX: Beautiful Hunter (wd:Q8042573): 1994 film by Masaru Konuma

[Assistant] The top result is the correct one: "Hunter × Hunter" (wd:Q696071). Now let's find out in which magazine it is published. We can search for properties related to publication or magazine for this entity.

[Tool]
Top 10 property alternatives:
1. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as wdt/p): larger work that a given work was published in, like a book, journal or music album, part of
2. publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as wdt/p): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
3. characters, also known as appears in this work (wd:P674 as wdt/p): characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games)
4. author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt/p): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
5. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
6. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/p): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
7. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
8. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
9. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
10. derivative work, also known as is source work of, is adapted as, is the basis for, iteration, reboot (wd:P4969 as wdt/p): new work of art (film, book, software, etc.) derived from major part of this work

No other items found

[Assistant] The property "published in" (wdt:P1433) seems to be the most relevant. Let's use this property to find the magazine in which "Hunter × Hunter" is published.

[Tool]
Got 1 row and 1 column:
| magazine                        |
| ------------------------------- |
| Weekly Shōnen Jump (wd:Q220015) |

[Assistant] The magazine in which "Hunter × Hunter" is published is "Weekly Shōnen Jump" (wd:Q220015). Next, we need to find when this magazine was established. We can search for properties related to establishment or founding date for this entity.

[Tool]
Top 10 property alternatives:
1. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
2. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
3. intended public, also known as for, user group, target market, target group, target demographic (wd:P2360 as wdt/p): this work, product, object or event is intended for, or has been designed to that person or group of people, animals, plants, etc
4. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
5. publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as wdt/p): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
6. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/p): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))

No other items found

[Assistant] The property "inception" (wdt:P571) seems to be the most relevant for finding the establishment date of "Weekly Shōnen Jump". Let's use this property to find the establishment date.

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1968-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The magazine "Weekly Shōnen Jump" was established on January 1, 1968.

Here is the final SPARQL query:

```sparql
SELECT ?date WHERE {
  wd:Q220015 wdt:P571 ?date .
}
```

And the answer to the question is: **January 1, 1968**.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected result. The magazine 'Weekly Shōnen Jump', where 'Hunter x Hunter' is published, was indeed established on January 1, 1968.