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

Using entities:
Python (wd:Q28865), also known as py, python 2, Python 2, Python 3, Python (computer language), etc.
programming language (wd:Q9143), also known as coding language, computer language, computer programming, computer programming language

Using properties:
subclass of (wd:P279 as wdt), also known as all members of this class also belong to, category of, form of, has superclass, is a class of, etc.
instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.

Answer: True — according to Wikidata, Python (wd:Q28865) is an instance of (directly or via a subclass) programming language (wd:Q9143).

Is Python a kind of Programming languages?

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] Is Python a kind of Programming languages?

[Assistant] Step 1: I'll search Wikidata for the entity corresponding to "Python" (the programming language), to get the exact item I should check. I will look for "Python (programming language)". I'll explain my reasoning and then run a search query.

[Tool]
Top 10 entity alternatives:
1. Python (wd:Q28865, matched via Python programming language), also known as py, python 2, Python 2, Python 3, Python (computer language), etc.: general-purpose, high-level programming language / general-purpose, high-level programming language / is instance of object-based language / general-purpose programming language / general-purpose programming language
2. Python: The future programming language (wd:Q113194464): scientific article published on 20 January 2022 / scientific article published on 20 January 2022 / scientific article published on 20 January 2022 / is instance of scholarly article / is instance of academic article
3. PYTHON: THE MOST ADVANCED PROGRAMMING LANGUAGE (wd:Q120764715): scientific article published in 2022 / is instance of scholarly article / is instance of academic article
4. Efficiency asynchronous application programming language Python (wd:Q113231212): scientific article published on 18 December 2018 / scientific article published on 18 December 2018 / scientific article published on 18 December 2018 / is instance of scholarly article / is instance of academic article
5. Type inference for Python programming language (wd:Q113263977): scientific article published on 25 November 2014 / scientific article published on 25 November 2014 / scientific article published on 25 November 2014 / is instance of scholarly article / is instance of academic article
6. Python as Multi Paradigm Programming Language (wd:Q113199030): scientific article published on 16 January 2020 / scientific article published on 16 January 2020 / scientific article published on 16 January 2020 / is instance of scholarly article / is instance of academic article
7. Python Programming/GUI Programming (wd:Q29529146)
8. Application of python programming language in measurements (wd:Q113222154): scientific article published on 08 February 2019 / is instance of scholarly article / is instance of academic article
9. On the Python programming language for statisticians (wd:Q113229894): scientific article published on 29 April 2020 / scientific article published on 29 April 2020 / scientific article published on 29 April 2020 / is instance of scholarly article / is instance of academic article
10. TEACHING ALGORITHMIZATION AND PROGRAMMING USING PYTHON LANGUAGE (wd:Q113264868): scientific article published on 17 June 2015 / scientific article published on 17 June 2015 / scientific article published on 17 June 2015 / is instance of scholarly article / is instance of academic article

[Assistant] Now I'll search for the Wikidata item for "programming language" so I can check whether Python is an instance of or subclass of that item. I'll run an entity search for "programming language".

[Tool]
Top 10 entity alternatives:
1. programming language (wd:Q9143), also known as coding language, computer language, computer programming, computer programming language: language for communicating instructions to a machine / is instance of computer science term / is subclass of computer language
2. C (wd:Q15777, matched via C programming language), also known as C programming language: is instance of procedural programming language / is instance of structured programming language / is instance of imperative programming language / is instance of computer science term / general-purpose programming language / is instance of programming language / is instance of compiled language
3. Java (wd:Q251, matched via java programming language), also known as java programming language: is instance of multi-paradigm programming language / object-oriented programming language / object-oriented programming language / is instance of JVM language / is instance of software
4. Python (wd:Q28865, matched via Python programming language), also known as py, python 2, Python 2, Python 3, Python (computer language), etc.: general-purpose, high-level programming language / general-purpose, high-level programming language / is instance of object-based language / general-purpose programming language / general-purpose programming language
5. PHP (wd:Q59, matched via PHP programming language), also known as Hypertext Preprocessor, Personal Home Page, php, PHP Hypertext Preprocessor, PHP: Hypertext Preprocessor, etc.: is instance of multi-paradigm programming language / scripting language focused on web development / is instance of object-based language / is instance of interpreted language
6. Ruby (wd:Q161053, matched via Ruby programming language), also known as rb, Ruby language, Ruby programming language: is instance of object-based language / general-purpose programming language
7. BASIC (wd:Q42979, matched via BASIC programming language), also known as BASIC programming language, Beginners’ All-purpose Symbolic Instruction Code, Symbolic Instruction Code: Introductory programming language, consisting primarily of English words or abbreviations of them / programming language for beginners, mainly using familiar English words or abbreviations of them / is instance of non-structured programming language / is instance of imperative programming language / is instance of programming language
8. Lisp (wd:Q132874, matched via Lisp (programming language)), also known as ISO/IEC 13816, JIS X 3012, LISP, Lisp (programming language), List Processor, etc.: functional programming language based on the lambda calculus / is instance of multi-paradigm programming language / is instance of functional programming language / is instance of reflective programming language / is instance of procedural programming language / is instance of metaprogramming language / is instance of interpreted language
9. R (wd:Q206904, matched via R programming language), also known as GNU R, GNU S, R language, R programming language: is instance of multi-paradigm programming language / programming language for statistical analysis / is instance of programming language / is instance of statistical package / is instance of field of study / is instance of free software / is instance of GNU package
10. Haskell (wd:Q34010, matched via Haskell programming language), also known as Haskell programming language, hs: is instance of purely functional programming language / is instance of non-strict programming language / is instance of modular programming language / purely functional programming language / is instance of off-side rule language / is instance of programming language / is instance of interpreted language / is instance of compiled language

[Assistant] I'll list the properties/triples of the Python item (wd:Q28865) to see how it's classified and which property expresses that it's a programming language (e.g., wdt:P31 instance of). I'll run a list query for that subject.

[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) | Freebase ID (wdt:P646)       | /m/05z1_                                                                                |
| 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) | GND ID (wdtn:P227)           | <https://d-nb.info/gnd/4434275-5>                                                              |
| Python (wd:Q28865) | copyright license (wdt:P275) | Python Software Foundation License (wd:Q2600299)                                               |
| ...                | ...                          | ...                                                                                |

[Assistant] Step: build an ASK query that checks whether the Wikidata item for Python (wd:Q28865) is an instance of programming language (wd:Q9143), or an instance of an item that is a subclass (P279*) of programming language. I'll now execute that ASK query to get a boolean result.

[Tool] True

[Assistant] The ASK query returned True, meaning Python is an instance of programming language (directly or via a class that's a subclass). I'll now prepare the final answer, showing the SPARQL query used and the result, and explain the steps. Then I'll call the answer function with the query and final statement.

[Tool] Stopping


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

Using entities:
Japanese (wd:Q5287), also known as Japanese language, Japanesic

Using properties:
number of speakers, writers, or signers (wd:P1098 as wdt), also known as signers of a language, speakers of language, writers of a language, P1098

Answer: True — according to Wikidata (wd:Q5287) the recorded number of speakers (wdt:P1098) for Japanese is greater than 100,000,000.

Do more than 100000000 people speak Japanese?

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] Do more than 100000000 people speak Japanese?

[Assistant] I will first search for the Wikidata item for the Japanese language, and then look for properties that give the number of speakers (e.g., "number of speakers" P1098). I'll explain each step and execute SPARQL queries as needed. I will now search for the Japanese language entity.

[Tool]
Top 10 entity alternatives:
1. Japanese (wd:Q5287, matched via Japanese language), also known as Japanese language, Japanesic: is instance of natural language / is instance of modern language / language spoken in East Asia / is subclass of Japonic / East Asian language
2. Japanese language (wd:Q10855582): is instance of school subject / 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 / is instance of Stack Exchange forum site
4. Japanese Wikipedia (wd:Q177837, matched via Japanese language Wikipedia), also known as ASIA, Japanese language Wikipedia, Japanese wikipedia, Japanese WP, jawiki, etc.: is instance of Wikipedia language edition / Japanese-language edition of Wikipedia
5. Japanese Sign Language (wd:Q35601), also known as JSL: is subclass of Japanese Sign Language family / is instance of sign language / sign language
6. Classical Japanese (wd:Q1332057, matched via Classical Japanese language), also known as Classical Japanese language: literary form of the Japanese language, standard until WW2, based on Heian-period Early Middle Japanese with later influences / is instance of classical language / is instance of literary language / is instance of sacred language / is subclass of Japanese
7. Japanese language education (wd:Q17214937), also known as teaching Japanese as a foreign language: is subclass of education of a specific language / is subclass of second language education / is subclass of language education
8. Japanese language department (wd:Q11086620): is instance of Academic department / is instance of academic department
9. dictionary of the Japanese language (wd:Q6158568, matched via Japanese language dictionary), also known as dictionary of Japanese, Japanese dictionary, Japanese language dictionary: is subclass of dictionary of a specific language / language version of dictionary
10. Thesaurus:penis (Japanese language) (wd:Q101144363), also known as Thesaurus:陰茎: is instance of Wiktionary thesaurus page

[Assistant] Next I'll search for properties that indicate number of speakers (e.g., "number of speakers"). I'll search for properties related to "number of speakers".

[Tool]
Top 10 property alternatives:
1. number of speakers, writers, or signers (wd:P1098 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as signers of a language, speakers of language, writers of a language, P1098: number of people who use a language
2. number of viewers/listeners (wd:P5436 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of listeners), also known as listen count, listener count, listener number, listeners, listens, etc.: number of viewers of a television or broadcasting program; web traffic on websites
3. spoken by (wd:P10894 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via speaker), also known as narrator, speaker, P10894: the person who is speaking in this audio or video file
4. speaker (wd:P823 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as speech by, spoken by, P823: person who is speaker for this event, ceremony, keynote, presentation or in a literary work / is subproperty of participant / is subproperty of spoken by
5. number of participants (wd:P1132 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as number of competitors, number of teams, participant count, participants, qty participants, etc.: number of participants of an event, e.g. people or groups of people that take part in the event (NO units) / is subproperty of quantity
6. number of seats (wd:P1342 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as membership quantity, number of seats (members), quantity of members, seats (members), P1342: total number of seats/members in an assembly (legislative house or similar) / number of seats/members in an assembly (legislative house or similar)
7. number of seats in assembly (wd:P1410 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of seats), also known as number of delegates, number of representatives, number of seats, seats, P1410: number of seats a political party, faction, or group has in a given assembly
8. maximum capacity (wd:P1083 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of seats), also known as capacity, complement, crew, number of seats, seating capacity, etc.: number of people allowed for a venue or vehicle / number of people allowed for a venue or vehicle
9. candidate number (wd:P4243 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of candidate), also known as candidate ID, election candidate number, ID of candidate, number of candidate, P4243: number of the candidate in an election
10. quantity (wd:P1114 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via total number), also known as amount, copies, count, instances, multiplicity, etc.: number of instances of this subject in the universe of the ... number of instances in Wikidata may be lower or higher) / number of instances of this subject

[Assistant] I'll check the Japanese language item wd:Q5287 for statements using P1098 "number of speakers".

[Tool]
Got 1 row and 3 columns:
| subject             | property                                            | object                  |
| ------------------- | --------------------------------------------------- | ----------------------- |
| Japanese (wd:Q5287) | number of speakers, writers, or signers (wdt:P1098) | 128000000 (xsd:decimal) |

[Assistant]
I'll run an ASK query that checks whether the Wikidata property "number of speakers" (P1098) for the Japanese language (wd:Q5287) is greater than 100000000. The query:

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

I'll execute this query now.

[Tool] True

[Assistant] The ASK query returned True, meaning Wikidata states that more than 100,000,000 people speak Japanese. I will now provide the final answer and include the SPARQL query I executed.

[Tool] Stopping


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?member ?memberLabel ?birthdate WHERE {
  wd:Q48817408 wdt:P161 ?member .
  ?member wdt:P569 ?birthdate .
  OPTIONAL {
    ?member rdfs:label ?memberLabel .
    FILTER ( LANG( ?memberLabel ) = "en" )
  }
}
ORDER BY ASC ( ?birthdate )
LIMIT 1

Using entities:
Queer Eye (wd:Q48817408)

Using properties:
cast member (wd:P161 as wdt), also known as actor, actress, contestant of a play, feat., film starring, etc.
date of birth (wd:P569 as wdt), also known as birth date, birthdate, birth year, birthyear, born, etc.

Answer: Karamo Brown (wd:Q44870529), born 1980-11-02, is the oldest cast member of the Netflix series "Queer Eye" (wd:Q48817408).

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

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

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

[Assistant] I will search Wikidata for the Netflix series "Queer Eye" to find its item identifier. Then I'll look for its cast members and retrieve their birth dates to compute who is the oldest. I'll start by searching for the series entity. I'll run a search for "Queer Eye".

[Tool]
Top 10 entity alternatives:
1. Queer Eye (wd:Q1418248), also known as Queer Eye for the Straight Guy: 2003 American reality television series / is instance of television series / is instance of serial
2. Queer Eye (wd:Q48817408): is instance of television series / 2018 American television series / is instance of serial
3. Queer Eye: Germany (wd:Q111914878), also known as Queer Eye Germany: is instance of television series / German reality television series / is instance of serial
4. Queer Eye, season 4 (wd:Q67649081): is instance of television series season / season of television series / is instance of series
5. Queer Lion 2018 (wd:Q56323749): is instance of recurrent event edition
6. Queer Eye, season 1 (wd:Q57312338): is instance of television series season / season of television series / is instance of series
7. Queer Eye, season 2 (wd:Q57313933): is instance of television series season / season of television series / is instance of series
8. Queer Eye, season 3 (wd:Q65590894): is instance of television series season / season of television series / is instance of series
9. Queer Eye, season 6 (wd:Q110791710): is instance of television series season / 6th season of the Netflix series / 6th season of Netflix series / is instance of series
10. Queer Eye, season 5 (wd:Q97455984): is instance of television series season / 5th season of Netflix series / is instance of series

[Assistant] I'll look up properties of the 2018 Netflix "Queer Eye" item (wd:Q48817408) to find its cast/starring property. I'll list triples for that subject.

[Tool]
Got 178 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                               | object                                                                         |
| ------------------------ | -------------------------------------- | ------------------------------------------------------------------------------ |
| Queer Eye (wd:Q48817408) | instance of (wdt:P31)                  | television series (wd:Q5398426)                                                |
| Queer Eye (wd:Q48817408) | Google Knowledge Graph ID (wdtn:P2671) | <http://g.co/kg/g/11gfndn54m>                                                  |
| Queer Eye (wd:Q48817408) | has part(s) (wdt:P527)                 | Queer Eye, season 6 (wd:Q110791710)                                            |
| Queer Eye (wd:Q48817408) | country of origin (wdt:P495)           | United States (wd:Q30)                                                         |
| Queer Eye (wd:Q48817408) | official website (wdt:P856)            | <https://www.netflix.com/title/80160037>                                       |
| Queer Eye (wd:Q48817408) | genre (wdt:P136)                       | reality television (wd:Q182415)                                                |
| Queer Eye (wd:Q48817408) | award received (wdt:P166)              | Primetime Emmy Award for Outstanding Structured Reality Program (wd:Q18153300) |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161)                 | Jonathan Van Ness (wd:Q50379405)                                               |
| Queer Eye (wd:Q48817408) | IMDb ID (wdt:P345)                     | tt7259746                                                                      |
| Queer Eye (wd:Q48817408) | start time (wdt:P580)                  | 2018-02-07T00:00:00Z (xsd:dateTime)                                            |
| ...                      | ...                                    | ...                                                                            |

[Assistant] I'll list the cast member (wdt:P161) triples for the series to get all cast items.

[Tool]
Got 6 rows and 3 columns:
| subject                  | property               | object                           |
| ------------------------ | ---------------------- | -------------------------------- |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Jonathan Van Ness (wd:Q50379405) |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Jeremiah Brent (wd:Q29452671)    |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Karamo Brown (wd:Q44870529)      |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Bobby Berk (wd:Q49729241)        |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Antoni Porowski (wd:Q50377216)   |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Tan France (wd:Q50379407)        |

[Assistant] I'll run a SPARQL query that gets all cast members (wdt:P161) of the Netflix Queer Eye item (wd:Q48817408), fetches their dates of birth (wdt:P569), retrieves English labels, orders by birthdate ascending (oldest first), and returns the earliest (LIMIT 1). Now I'll execute the query.

[Tool]
Got 1 row and 3 columns:
| member                      | memberLabel       | birthdate                           |
| --------------------------- | ----------------- | ----------------------------------- |
| Karamo Brown (wd:Q44870529) | Karamo Brown (en) | 1980-11-02T00:00:00Z (xsd:dateTime) |

[Assistant] The query returned Karamo Brown as the oldest cast member (born 1980-11-02). I'll prepare the final SPARQL query and answer. Before finishing, I'll re-run a query that returns all cast members with their birthdates for verification.

[Tool]
Got 6 rows and 3 columns:
| member                           | memberLabel            | birthdate                           |
| -------------------------------- | ---------------------- | ----------------------------------- |
| Karamo Brown (wd:Q44870529)      | Karamo Brown (en)      | 1980-11-02T00:00:00Z (xsd:dateTime) |
| Bobby Berk (wd:Q49729241)        | Bobby Berk (en)        | 1982-08-25T00:00:00Z (xsd:dateTime) |
| Tan France (wd:Q50379407)        | Tan France (en)        | 1983-04-20T00:00:00Z (xsd:dateTime) |
| Antoni Porowski (wd:Q50377216)   | Antoni Porowski (en)   | 1984-03-14T00:00:00Z (xsd:dateTime) |
| Jeremiah Brent (wd:Q29452671)    | Jeremiah Brent (en)    | 1984-11-24T00:00:00Z (xsd:dateTime) |
| Jonathan Van Ness (wd:Q50379405) | Jonathan Van Ness (en) | 1987-03-28T00:00:00Z (xsd:dateTime) |

[Assistant] The results confirm Karamo Brown is the oldest. I'll now send the final SPARQL query and answer.

[Tool] Stopping


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?magazine ?magazineLabel ?inception WHERE {
  wd:Q696071 wdt:P1433 ?magazine .
  OPTIONAL {
    ?magazine rdfs:label ?magazineLabel FILTER ( LANG( ?magazineLabel ) = "en" )
  }
  OPTIONAL {
    ?magazine wdt:P571 ?inception
  }
}

Using entities:
Hunter × Hunter (wd:Q696071), also known as HUNTER × HUNTER, Hunter x Hunter, HXH

Using properties:
published in (wd:P1433 as wdt), also known as album, article of, chapter of, essay of, music album, etc.
inception (wd:P571 as wdt), also known as broke ground, built, commenced on date, commencement date, completed, etc.

Answer: The magazine is Weekly Shōnen Jump (wd:Q220015). It was established (inception) on 1968-01-01.

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

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

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

[Assistant] Step 1: I'll search for the Wikidata item for "Hunter x Hunter" to identify the work and the magazine property used (published in). I'll look up the entity first.

[Tool]
Top 10 entity alternatives:
1. Hunter × Hunter (wd:Q696071), also known as HUNTER × HUNTER, Hunter x Hunter, HXH: is instance of manga series / Japanese manga series
2. Hunter × Hunter (wd:Q70209136), also known as H×H, Hunter x Hunter, HxH: is instance of anime television series / 2011 Japanese anime television series
3. Hunter × Hunter (wd:Q21232458), also known as Hunter x Hunter, HxH: is instance of anime television series / 1999 Japanese anime television series
4. Hunter × Hunter (wd:Q132542678), also known as Hunter×Hunter: is instance of media franchise / media franchise
5. Hunter × Hunter (wd:Q132543073), also known as Hunter×Hunter: is instance of video game series / video game series
6. Combination × And × Evolution (wd:Q116849879, matched via Hunter × Hunter ep99), also known as Combination × to × Evolution, Hunter × Hunter ep 99, Hunter × Hunter ep. 99, Hunter × Hunter ep99, Hunter × Hunter Episode 99: is instance of anime television series episode / Episode 99 of Hunter × Hunter
7. Knov × And × Morel (wd:Q116849888, matched via Hunter × Hunter ep6), also known as Hunter × Hunter ep 6, Hunter × Hunter ep. 6, Hunter × Hunter ep6, Hunter × Hunter Episode 6, Knov × to × Morel: is instance of anime television series episode / Episode 6 of Hunter × Hunter
8. Resolve × And × Awakening (wd:Q116849887, matched via Hunter × Hunter ep5), also known as Hunter × Hunter ep 5, Hunter × Hunter ep. 5, Hunter × Hunter ep5, Hunter × Hunter Episode 5, Kakugo × to × Kakusei: is instance of anime television series episode / Episode 5 of Hunter × Hunter
9. Doubt × And × Hesitation (wd:Q116849886, matched via Hunter × Hunter ep4), also known as Hunter × Hunter ep 4, Hunter × Hunter ep. 4, Hunter × Hunter ep4, Hunter × Hunter Episode 4, Mayoi × to × Tomadoi: is instance of anime television series episode / Episode 4 of Hunter × Hunter
10. Check × And × Mate (wd:Q116849884, matched via Hunter × Hunter ep3), also known as Hunter × Hunter ep 3, Hunter × Hunter ep. 3, Hunter × Hunter ep3, Hunter × Hunter Episode 3, Tsumi × to × Yomi: is instance of anime television series episode / Episode 3 of Hunter × Hunter

[Assistant] Next I'll search for properties of the Hunter × Hunter (manga) entity that relate to publication or the magazine it's published in — e.g., "published in", "publication", "serialised in". I'll query property suggestions for that entity.

[Tool]
Top 10 property alternatives:
1. published in (wd:P1433 as p/wdt), also known as album, article of, chapter of, essay of, music album, etc.: larger work that a given work was published in, like a journal, a website, a collection, a book or a music album / larger work that a given work was published in / is subproperty of part of
2. publisher (wd:P123 as p/wdt), also known as board game publisher, book publisher, comic book publisher, comic publisher, music publisher, etc.: organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software / organisation or person responsible for publishing books, periodicals, games or software / organization or person responsible for publishing books, periodicals, games or software
3. characters (wd:P674 as p/wdt, matched via appears in this work), also known as appears in this work, P674: characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games) / characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games) / characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games)
4. start time (wd:P580 as p/wdt, matched via joined), also known as began, beginning, building date, effective, effectivity, etc.: indicates the time an item begins to exist or a statement starts being valid / indicates the time an item begins to exist or a statement starts being valid / time an entity begins to exist or a statement starts being valid / is subproperty of point in time
5. derivative work (wd:P4969 as p/wdt, matched via cover), also known as adaptation, adapted as, cover, derived work, has adaptation, etc.: work created from major part of this artwork; work created from major part of this software / new work of art (film, book, software, etc.) derived from major part of this work
6. logo image (wd:P154 as p/wdt, matched via mark), also known as insignia, logo, logomark, mark, marque, etc.: graphic mark or emblem commonly used by commercial enterprises, organisations and products / graphic mark or emblem commonly used by commercial enterprises, organisations and products / graphic mark or emblem commonly used by commercial enterprises, organizations and products / graphic mark or emblem commonly used by commercial enterprises, organizations and products / is subproperty of icon
7. official website (wd:P856 as p/wdt, matched via official page), also known as home page, homepage, home page (official), homepage (official), official homepage, etc.: URL of the official page of an item (current or former). ... see the "Hijacked or dead websites" section of the Talk page / is subproperty of URL
8. author (wd:P50 as p/wdt), also known as co-author, creator, maker, playwright, poet, etc.: main creator(s) of a written work (use on works, not humans); ... name string) when Wikidata item is unknown or does not exist / main creator(s) of a written work (use on works, not humans) / main creator(s) of a written work (use on works, not humans) / is subproperty of creator
9. genre (wd:P136 as p/wdt, matched via P136), also known as artistic genre, art style, film genre, genre of literature, genre of music, etc.: creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic / genre of a creative work or genre in which an artist works
10. different from (wd:P1889 as p/wdt, matched via not), also known as confused with, differs from, disambiguated from, distinct from, distinguished from, etc.: item that is different from another item, with which it is often confused / item that is different from another item, with which it may be confused

No other items found

[Assistant] Step 2: I'll query the published in (P1433) value for the manga Hunter × Hunter to get the magazine entity.

[Tool]
Got 1 row and 2 columns:
| magazine                        | magazineLabel           |
| ------------------------------- | ----------------------- |
| Weekly Shōnen Jump (wd:Q220015) | Weekly Shōnen Jump (en) |

[Assistant] Step 3: I'll check which property on Wikidata corresponds to "established" / "inception" to use and verify it exists (likely P571). Then I'll query the inception (established) date for Weekly Shōnen Jump (wd:Q220015).

[Tool]
Top 10 property alternatives:
1. inception (wd:P571 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as broke ground, built, commenced on date, commencement date, completed, etc.: time when an entity begins to exist; for date of official opening use P1619 / time when an entity begins to exist; for date of official opening use P1619 / date or point in time when the organisation / object was founded / created / is subproperty of start time
2. production company (wd:P272 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via movie studio), also known as ballet company, broadcasting company, film studio, motion picture studio, movie studio, etc.: company that produced this film, audio or performing arts work / company that produced this film, audio or performing arts work
3. of (wd:P642 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via in), also known as applies to, for, in, in scope of, in the scope of, etc.: (This property is being deprecated, see details at WD:P642) ... a statement applies within the scope of a particular item / (This property is being deprecated, see details at WD:P642) ... a statement applies within the scope of a particular item / (This property is being deprecated, see details at WD:P642) ... a statement applies within the scope of a particular item / (being deprecated, find alternatives at WD:P642) qualifier ... a statement applies within the scope of a particular item
4. location (wd:P276 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via in), also known as based in, city, from, held by, in, etc.: location of the object, structure or event. In the case of an ... use P706. Use P7153 for locations associated with the object / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706.
5. part of (wd:P361 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via in), also known as assembly of, branch of, chain, collateral branch of, component of, etc.: object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670))
6. located in the administrative territorial entity (wd:P131 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via in), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / is subproperty of location / is subproperty of part of
7. last entry (wd:P10818 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via last entrance), also known as last admission, last entrance, P10818: time after which an establishment or attraction no longer admits entry, qualifier for P3025 (for closing time, use P8627)
8. International Nuclear Event Scale (wd:P2127 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via INES), also known as INES, P2127: international scale for rating nuclear events and accidents
9. first flight (wd:P606 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via first launch), also known as 1st flight, date of the first flight, FF, first launch, maiden flight, etc.: date or point in time on which aircraft, rocket, or airline first flew / is subproperty of significant event
10. derivative work (wd:P4969 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via incarnation), also known as adaptation, adapted as, cover, derived work, has adaptation, etc.: work created from major part of this artwork; work created from major part of this software / new work of art (film, book, software, etc.) derived from major part of this work

[Assistant] I'll query Weekly Shōnen Jump (wd:Q220015) for its inception (P571) date.

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

[Assistant] The inception date for Weekly Shōnen Jump is 1968-01-01. I'll now prepare the final SPARQL query that returns the magazine and its inception date starting from Hunter × Hunter. Per the rules, the query should return IRIs and optionally labels in OPTIONAL clauses. I'll include the magazine IRI and its inception. I'll also include the magazine label as optional. Then I'll execute it to make sure it returns the expected result.

[Tool]
Got 1 row and 3 columns:
| magazine                        | magazineLabel           | inception                           |
| ------------------------------- | ----------------------- | ----------------------------------- |
| Weekly Shōnen Jump (wd:Q220015) | Weekly Shōnen Jump (en) | 1968-01-01T00:00:00Z (xsd:dateTime) |

[Assistant] Now I'll provide the final answer with the SPARQL query and the extracted result.

[Tool] Stopping