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

Yes, more than 100,000,000 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 have access to the following knowledge graphs:
wikidata at http://amur:7001

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]
First, I need to identify the entity for "Japanese" (the language) in Wikidata, and then find the property that indicates the number of speakers. Finally, I will check if the number of speakers is greater than 100,000,000.

Step 1: Search for the entity "Japanese language" in Wikidata.

[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 most relevant entity for "Japanese language" is wd:Q5287.

Next, I need to find the property that indicates the number of speakers for a language. I'll search for properties related to "number of speakers".

[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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): number of words in text
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqn/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): language designated as official by this item, language used
5. speaker, also known as speech by, spoken by (wd:P823 as pqn/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): number of entities that are part of an organization at a particular time

[Assistant]
The most relevant property is "number of speakers" (wdt:P1098).

Now, I will construct an ASK query to check if the number of speakers for Japanese (wd:Q5287) is greater than 100,000,000.

[Tool] True

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct for the question. It uses an ASK query to check if the number of speakers of Japanese (wd:Q5287) is greater than 100,000,000 using the appropriate property (wdt:P1098). The query returns a boolean as required for a yes/no question. No further refinement is needed.


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

The oldest cast member of the Netflix show 'Queer Eye' according to Wikidata is Karamo Brown (wd:Q44870529), born on November 2, 1980. This is based on all cast members currently linked to the Netflix version in Wikidata.

[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 http://amur:7001

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 break down the question:

1. We need to identify the Netflix show "Queer Eye" in Wikidata.
2. We need to find its cast members.
3. For each cast member, we need to find their date of birth.
4. We need to determine which cast member is the oldest (i.e., has the earliest date of birth).

Let's start by searching for the entity for "Queer Eye" in Wikidata.

[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 relevant entity for the Netflix show "Queer Eye" is wd:Q48817408 (2018 American television series).

Next, I need to find the cast members of this show. I'll search for properties related to "cast member" or similar for this entity.

[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 for "cast member" is wd:P161. I will now list the cast members of "Queer Eye" (wd:Q48817408) using this property.

[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) | Antoni Porowski (wd:Q50377216)   |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Bobby Berk (wd:Q49729241)        |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Karamo Brown (wd:Q44870529)      |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Tan France (wd:Q50379407)        |
| Queer Eye (wd:Q48817408) | cast member (wdt:P161) | Jeremiah Brent (wd:Q29452671)    |

[Assistant]
The main cast members of "Queer Eye" according to Wikidata are:
- Jonathan Van Ness (wd:Q50379405)
- Antoni Porowski (wd:Q50377216)
- Bobby Berk (wd:Q49729241)
- Karamo Brown (wd:Q44870529)
- Tan France (wd:Q50379407)
- Jeremiah Brent (wd:Q29452671)

Next, I need to get the date of birth for each of these cast members. The property for date of birth is likely "date of birth" (P569). I will confirm this property.

[Tool]
Top 10 property alternatives:
1. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pqn/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): 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/psn/pq/pqv/prv/ps/wdtn/psv/pr/p/prn/wdt): alias used by someone (for nickname use P1449), name

[Assistant] The property for "date of birth" is wd:P569. I will now construct a query to get the date of birth for each cast member and select the one with the earliest date (the oldest).

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

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

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The answer is incorrect. The SPARQL query only considers a hardcoded list of six people, but the cast of 'Queer Eye' has changed over time (e.g., the original cast and the Netflix reboot cast). The query should first identify all cast members of the Netflix version of 'Queer Eye' using appropriate properties (such as 'cast member' or 'member of' and linking to the correct show entity), and then select the oldest by date of birth. Additionally, the query should ensure it is only considering the Netflix version, not the original series. Please revise the query to dynamically retrieve all relevant cast members and then select the oldest.

[Assistant]
Thank you for the feedback. You are correct: the previous approach only considered a hardcoded list of cast members, which is not robust or future-proof. To address this, I need to:

1. Dynamically retrieve all cast members of the Netflix version of "Queer Eye" (wd:Q48817408) using the appropriate property (likely "cast member" wd:P161).
2. For each cast member, retrieve their date of birth (wd:P569).
3. Select the oldest (earliest date of birth).
4. Ensure that only cast members of the Netflix version (wd:Q48817408) are considered, not the original series or other adaptations.

Let's construct a SPARQL query that does this step by step.

First, I will check if there are any nuances in how "cast member" is used for the Netflix version, and confirm that wd:P161 is the correct property for this show.

[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) | has part(s) (wdt:P527)                          | Queer Eye, season 1 (wd:Q57312338)                                             |
| 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) | start time (wdt:P580)                           | 2018-02-07T00:00:00Z (xsd:dateTime)                                            |
| Queer Eye (wd:Q48817408) | social media followers (wdt:P8687)              | 430422 (xsd:decimal)                                                           |
| Queer Eye (wd:Q48817408) | original language of film or TV show (wdt:P364) | American English (wd:Q7976)                                                    |
| ...                      | ...                                             | ...                                                                            |

[Assistant]
The property "cast member" (wdt:P161) is indeed used for the Netflix version of "Queer Eye" (wd:Q48817408). Therefore, I can dynamically retrieve all cast members of this show using this property.

Now, I will write a SPARQL query that:
- Retrieves all cast members of wd:Q48817408 via wdt:P161.
- Gets their date of birth (wdt:P569).
- Optionally retrieves their English label.
- Orders by date of birth ascending and limits to the oldest.

Let's proceed with this improved query.

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

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

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is almost correct, but it orders the cast members by ascending date of birth, which means it returns the youngest, not the oldest, cast member. To find the oldest cast member, the query should order by descending date of birth (ORDER BY DESC(?dob)) and select the last one, or more simply, order by ascending date of birth (ORDER BY ASC(?dob)) and take the first result, which is correct. However, the answer claims Karamo Brown is the oldest, but he was born in 1980, and other main cast members (e.g., Jonathan Van Ness, Bobby Berk, Tan France, Antoni Porowski) may have different birth years. The query should be double-checked for completeness, ensuring all main cast members are included and that no one older is missing. Also, the query should return the IRIs as required, and optionally include labels using OPTIONAL { ?person rdfs:label ?label }. Please verify the completeness of the cast list and ensure the answer is accurate.

[Assistant]
Thank you for the detailed feedback. Let's carefully verify the completeness of the cast list and ensure the answer is accurate.

Step-by-step plan:
1. Dynamically retrieve all cast members of the Netflix "Queer Eye" (wd:Q48817408) using wdt:P161.
2. For each cast member, retrieve their date of birth (wdt:P569).
3. Optionally, retrieve their English label.
4. Order by ascending date of birth (oldest first) and take the first result.
5. Double-check that all main cast members (including any possible older guest or recurring cast) are included.

Let me first check how many unique cast members are returned for the Netflix version, and what their birthdates are, to ensure completeness.

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

[Assistant]
The query returns six cast members for the Netflix version of "Queer Eye" (wd:Q48817408), with the following birthdates:

1. Karamo Brown (wd:Q44870529): 1980-11-02
2. Bobby Berk (wd:Q49729241): 1982-08-25
3. Tan France (wd:Q50379407): 1983-04-20
4. Antoni Porowski (wd:Q50377216): 1984-03-14
5. Jeremiah Brent (wd:Q29452671): 1984-11-24
6. Jonathan Van Ness (wd:Q50379405): 1987-03-28

Karamo Brown is the oldest among these, born in 1980. This list includes all main and recurring cast members currently linked to the Netflix version in Wikidata. If there were any older cast members, they would appear at the top of this list.

The query returns IRIs as required, and labels are included optionally.

Here is the final, robust SPARQL query and answer:

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?magazine ?inception WHERE {
  wd:Q696071 wdt:P1433 ?magazine .
  ?magazine wdt:P571 ?inception
}

The magazine in which Hunter x Hunter is published, Weekly Shōnen Jump, was established on 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 http://amur:7001

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 break down the question:

1. The user wants to know the establishment date of the magazine in which "Hunter x Hunter" is published.
2. First, I need to identify the entity for "Hunter x Hunter".
3. Then, I need to find the property that links "Hunter x Hunter" to its magazine of publication.
4. Next, I need to identify the magazine entity.
5. Finally, I need to find the property for the establishment date of the magazine.

Let's start by searching 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 most relevant entity for "Hunter x Hunter" as a manga series is wd:Q696071.

Next, I need to find the property that links this manga series to its magazine of publication. I will search for properties related to "magazine" or "publication" 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. 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
4. 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
5. 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
6. 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
7. 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
8. 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))
9. 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
10. 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

No other items found

[Assistant]
The property "published in" (wdt:P1433) is used to indicate the larger work (such as a magazine) in which a given work (such as a manga series) is published.

Next, I will check which magazine "Hunter x Hunter" (wd:Q696071) is published in using this property.

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

[Assistant]
"Hunter x Hunter" is published in "Weekly Shōnen Jump" (wd:Q220015).

Now, I need to find the property that gives the establishment date of a magazine. I will search for properties related to "establishment date" or "founded" for the entity "Weekly Shōnen Jump".

[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) is used for the date when an entity (such as a magazine) was established or began to exist.

Now, I will query the inception date for "Weekly Shōnen Jump" (wd:Q220015).

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the magazine in which Hunter x Hunter is published by using the 'published in' property (wdt:P1433) and retrieves its inception date (wdt:P571). The result matches the expected answer, and the query returns the actual IRI of the magazine as required. No further refinement is needed.