PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?distributor ?distributorLabel WHERE {
  wd:Q70209136 wdt:P750 ?distributor .
  OPTIONAL {
    ?distributor rdfs:label ?distributorLabel FILTER ( LANG( ?distributorLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| distributor               | distributorLabel |
| ------------------------- | ---------------- |
| Crunchyroll (wd:Q1142035) | Crunchyroll (en) |
| Hulu (wd:Q1630304)        | Hulu (en)        |
| Netflix (wd:Q907311)      | Netflix (en)     |

The Hunter × Hunter 2011 anime series can be watched on the following video streaming services: Crunchyroll, Hulu, and Netflix.

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

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

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

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

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

[User] on which video streaming services can i watch hunter x hunter anime series?

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

[Tool]
Example 1:
Question:
Which rockets were launched from Baikonur?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P279 * wd:Q41291 .
  ?uri wdt:P1427 wd:Q177477 .
}

Using entities:
Baikonur Cosmodrome, also known as 5 GIK, Baykonur Cosmodrome, GIK-5, State Test Range No. 5, Tyuratam (wd:Q177477): cosmodrome in Kazakhstan, used by Russia
rocket, also known as rockets (wd:Q41291): pyrokinetic engine used for propulsion; for the incendiary weapon, see Q2037215

Using properties:
start point, also known as start location, launch pad, launch site, starting place, starting point (wd:P1427 as wdt): starting place of this journey, flight, voyage, trek, migration etc., source of transfer, location
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 2:
Question:
Who was the wife of President Lincoln?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q91 wdt:P26 ?o1 .
}

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

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

Example 3:
Question:
Where do the Red Sox play?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q213959 wdt:P115 ?uri
}

Using entities:
Boston Red Sox, also known as Sox, redsoxs, RedSox, Red Sox, redsox (wd:Q213959): baseball team and Major League Baseball franchise in Boston, Massachusetts, United States

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

[Assistant] The examples do not directly relate to video streaming services or anime series. I will now search for the entity "Hunter x Hunter" to find its Wikidata identifier.

[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]
There are multiple entities for Hunter x Hunter. The relevant ones for the anime series are:
- Hunter × Hunter 2011 Japanese anime television series (wd:Q70209136)
- Hunter × Hunter 1999 Japanese anime television series (wd:Q21232458)

Next, I will search for properties related to video streaming services or platforms where these series can be watched. I will start by searching for properties related to "streaming service" or "video streaming".

[Tool]
Top 10 property alternatives:
1. streaming media URL, also known as archives, streaming url (wd:P963 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): URL where the subject's media stream exists, URL
2. broadcast by, also known as streamed by, TV station, TV network, TV channel, radio station (wd:P3301 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): channel, network, website or service that broadcast this item over radio, television or the Internet
3. online service, also known as ISP, internet service provider (wd:P2361 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): online service or online service provider tied to an item
4. YouTube video ID, also known as YT video ID, streaming url, yt video, Youtube video website, YouTube video link (wd:P1651 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): identifier of a video on YouTube; qualify trailers with "object ...er" (Q622550). For channels, use P2397; for playlists, use P4300, streaming media URL
5. Google Play Store app ID, also known as Google Play Store package, Play Store identifier, Play Store ID, PlayStore, Play Store (wd:P3418 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): package name of an app registered on Google Play
6. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): person, profession, organization or entity that operates the equipment, facility, or service, used by
7. Ustream username (wd:P4017 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): this item's username on Ustream, website username or ID
8. service options (wd:P11424 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): options for eating at a restaurant, café, etc
9. Every Noise at Once ID, also known as Spotify genre, Every Noise at Once identifier, everynoise.com identifier (wd:P9881 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): identifier of a music genre, style, or scene on the Every Noise at Once website
10. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): network(s) or service(s) that originally broadcast a radio or television program, broadcast by

[Assistant] The property "broadcast by" (wdt:P3301) seems relevant as it can indicate the channel, network, website, or service that broadcast or streamed the item. I will now check the values of this property for the Hunter × Hunter 2011 anime series (wd:Q70209136) to find the video streaming services.

[Tool] Got no rows and 2 columns

[Assistant] There are no direct values for the property "broadcast by" for the Hunter × Hunter 2011 anime series. I will try the same for the 1999 anime series (wd:Q21232458) to see if there are any video streaming services listed there.

[Tool] Got no rows and 2 columns

[Assistant] There are also no direct values for the property "broadcast by" for the Hunter × Hunter 1999 anime series. I will now try another property "streaming media URL" (wdt:P963) which might contain URLs to streaming services for the 2011 anime series.

[Tool] Got no rows and 1 columns

[Assistant] There are no streaming media URLs listed for the 2011 anime series either. I will try the same for the 1999 anime series.

[Tool] Got no rows and 1 columns

[Assistant] There are no streaming media URLs listed for the 1999 anime series either. I will now try to find video streaming services that have Hunter x Hunter in their catalog by searching for entities related to "video streaming service" and then checking if they have Hunter x Hunter in their offerings. I will start by searching for entities related to "video streaming service".

[Tool]
Top 10 entity alternatives:
1. video streaming service, also known as live streaming service website (wd:Q59152282): service that delivers video content for real-time viewing via the Internet
2. video streaming service app, also known as VOD app (wd:Q122538751): video streaming service presented through a mobile phone application
3. video game streaming service (wd:Q102337068)
4. Video streaming service and CD sales (wd:Q108808652): scientific article
5. Video curation service for personal streaming (wd:Q121085963): US patent 11410702
6. Quality of service for a video streaming service (wd:Q119326623): US patent 11356566
7. streaming service, also known as streaming website, streaming site, streaming media service, internet streaming service, online streaming service (wd:Q63241860): service that delivers on-demand media content via the Internet
8. Video Service, also known as VIDEO Service Co.,ltd. (wd:Q11330842)
9. Co-streaming within a live interactive video game streaming service (wd:Q118323856): US patent 11172012
10. Dynamic custom interstitial tran...eos for video streaming services (wd:Q119072461): US patent 11388452

[Assistant] The entity "video streaming service" (wd:Q59152282) seems to be the general class for video streaming services. I will now find instances or subclasses of this entity to get specific video streaming services.

[Tool]
Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| service                                  | serviceLabel                  |
| ---------------------------------------- | ----------------------------- |
| Exxen (wd:Q100250512)                    | Exxen (en)                    |
| The Roku Channel (wd:Q100254268)         | The Roku Channel (en)         |
| Flirt4Free (wd:Q100361079)               | Flirt4Free (en)               |
| ImLive (wd:Q100361518)                   | ImLive (en)                   |
| 1+1 video (wd:Q100997959)                | 1+1 video (en)                |
| ...                                      | ...                           |
| Zuvvii (wd:Q109326343)                   | Zuvvii (en)                   |
| Chorki (wd:Q109354463)                   | Chorki (en)                   |
| Nippon TV live streaming (wd:Q109356911) | Nippon TV live streaming (en) |
| WOWOW On Demand (wd:Q109358500)          | WOWOW On Demand (en)          |
| KlikFilm (wd:Q109430794)                 | KlikFilm (en)                 |

[Assistant] I have found a list of video streaming services. I will now check if any of these services have a property indicating that they offer the Hunter x Hunter anime series. I will start by checking if there is a property that links a video streaming service to the content it offers. I will search for properties related to "offers" or "content".

[Tool]
Top 10 property alternatives:
1. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): person, profession, organization or entity that operates the equipment, facility, or service, used by
2. has goal, also known as intention, mission, objective, objective of project or action, project of (wd:P3712 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): desired result or outcome
3. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): published price listed or paid for a product (use with unit of currency)
4. has command line option, also known as command line option, option (wd:P4837 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): an option which is accepted by the software from the command line
5. full work available at URL, also known as full text available at, full text available at URL, full text url, online mirror, online version (wd:P953 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): URL of a web page containing the full body of this item, URL
6. item of property constraint, also known as claim value, value, qid, property value, item qualifier (wd:P2305 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): qualifier to define a property constraint in combination with "property constraint" (P2302)
7. prize money, also known as money, purse, value (wd:P2121 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): amount in a specific currency
8. numeric value, also known as numerical value, value (wd:P1181 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): numerical value of a number, a mathematical constant, or a physical constant
9. units sold, also known as total sales, sales figures, sales, number of sales (wd:P2664 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): sales figures of an object, quantity
10. total revenue, also known as turnover, sales, revenue, income, gross revenue (wd:P2139 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): income gained by an organization during a given time frame. Not to be confused with fiscal revenue

[Assistant] There is no direct property indicating that a video streaming service offers a specific content. I will try another approach: I will check if the Hunter × Hunter anime series has any property indicating the platforms or services where it is available. I will search for properties of the 2011 anime series related to "available", "platform", or "service".

[Tool]
Top 10 property alternatives:
1. start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/p): time an entity begins to exist or a statement starts being valid, point in time
2. 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).
3. distributed by, also known as distributor (wd:P750 as wdt/p): distributor of a creative work; distributor for a record label; news agency; film distributor
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. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. 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
7. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
8. 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
9. X (Twitter) username, also known as twitter.com/, X username, X handle, x.com/, X account (wd:P2002 as wdt/p): username on X (formerly Twitter); do not include the '@' symbol, website username or ID
10. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as wdt/p): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

No other items found

[Assistant] There is a property "distributed by" (wdt:P750) which might indicate distributors or platforms distributing the anime series. I will check the values of this property for the Hunter × Hunter 2011 anime series.

[Tool]
Got 3 rows and 2 columns:
| distributor               | distributorLabel |
| ------------------------- | ---------------- |
| Crunchyroll (wd:Q1142035) | Crunchyroll (en) |
| Hulu (wd:Q1630304)        | Hulu (en)        |
| Netflix (wd:Q907311)      | Netflix (en)     |

[Assistant] The Hunter × Hunter 2011 anime series is distributed by Crunchyroll, Hulu, and Netflix. These are video streaming services where you can watch the Hunter x Hunter anime series. I will now provide this as the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the distributors of the Hunter × Hunter 2011 anime series, which correspond to the video streaming services where it can be watched. The answer lists Crunchyroll, Hulu, and Netflix, matching the query results. The query uses the appropriate property (wdt:P750) and entity (wd:Q70209136) and includes English labels for readability. The output is accurate, complete, and follows the guidelines for returning identifiers and labels. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?inceptionDate WHERE {
  wd:Q1420480 wdt:P571 ?inceptionDate
}

The first Ironman World Championship took place in the year 1978.

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

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

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

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

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

[User] when is the first ironman world championship?

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

[Tool]
Example 1:
Question:
Give me the Apollo 14 astronauts.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q178871 wdt:P1029 ?uri
}

Using entities:
Apollo 14, also known as Apollo XIV (wd:Q178871): third Moon landing and eighth crewed flight of the United States Apollo program

Using properties:
crew member, also known as crewmember (wd:P1029 as wdt): person that participated operating or serving aboard this vehicle

Example 2:
Question:
Which species does an elephant belong?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q7378 wdt:P279 ?uri .
}

Using entities:
elephant (wd:Q7378): large terrestrial mammals with trunks from Africa and Asia

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 3:
Question:
Who was the doctoral supervisor of Albert Einstein?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q937 wdt:P184 ?uri
}

Using entities:
Albert Einstein (wd:Q937): German-born theoretical physicist (1879–1955), physicist

Using properties:
doctoral advisor, also known as PhD supervisor, promotor, supervisor, thesis advisor, advisor (wd:P184 as wdt): person who supervised the doctorate or PhD thesis of the subject, supervised by, student of

[Assistant] The examples show how to query for specific events or entities related to a known entity. Now, I will identify the entity for "Ironman World Championship" in Wikidata and then find the property related to the date or time of the event.

[Tool]
Top 10 entity alternatives:
1. Ironman World Championship (wd:Q1420480): triathlon
2. 2009 Ironman World Championship (wd:Q1627953)
3. 2010 Ironman World Championship (wd:Q949501)
4. 2011 Ironman World Championship (wd:Q1144158): Held in Kailua-Kona, Hawaii
5. 2019 Ironman World Championship (wd:Q61081177)
6. 2007 Ironman World Championship, also known as 2007 Ford Ironman World Championship (wd:Q3652214)
7. 2008 Ironman World Championship (wd:Q1325961)
8. 2018 Ironman World Championship (wd:Q57699330)
9. 2006 Ironman World Championship (wd:Q3078193)
10. 2005 Ironman World Championship (wd:Q2122612)

[Assistant] The entity "Ironman World Championship" (wd:Q1420480) corresponds to the triathlon event. Next, I will search for properties related to the date or time of this event to find when the first Ironman World Championship took place.

[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. event interval, also known as event frequency, frequency of event, interval, period (wd:P2257 as wdt/p): standard nominal interval between scheduled or regularly recurri...1/(event frequency). Time period of periodically occurring event
3. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
4. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
5. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdt/wdtn/p): identifier from an international authority file of names, subjects, and organizations
6. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as wdt/p): item that is different from another item, with which it may be confused
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
9. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category

No other items found

[Assistant] The property "inception" (wdt:P571) seems to be the most relevant for the date when the Ironman World Championship began. I will now query for the inception date of the Ironman World Championship (wd:Q1420480).

[Tool]
Got 1 row and 1 column:
| inceptionDate                       |
| ----------------------------------- |
| 1978-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly identifies the year 1978 as the inception date of the Ironman World Championship, which matches the SPARQL query result. The query uses the property P571 (inception date) for the entity Ironman World Championship (Q1420480), which is appropriate for determining when the event first took place. The query returns the date in a standard format, and the answer is clear and accurate. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?competition ) AS ?winCount ) WHERE {
  wd:Q676899 wdt:P2522 ?competition .
  ?competition rdfs:label ?label .
  FILTER ( CONTAINS( LCASE( ?label ) , "fifa world cup" ) ) FILTER ( LANG( ?label ) = "en" )
}

Got 1 row and 1 column:
| winCount    |
| ----------- |
| 4 (xsd:int) |

The Italian national soccer team has won the FIFA World Cup 4 times.

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

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

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

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

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

[User] How many times did the Italian national soccer team win the Fifa World Cup?

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

[Tool]
Example 1:
Question:
In which city did Nikos Kazantzakis die?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q214622 wdt:P20 ?uri
}

Using entities:
Nikos Kazantzakis (wd:Q214622): Greek writer, poet and philosopher (1883-1957), children's writer, correspondent, travel writer, lexicographer, prose writer, screenwriter, philosopher, politician, translator, playwright, journalist, novelist, traveler, writer, poet

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

Example 2:
Question:
Who is the mayor of Rotterdam?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q34370 wdt:P6 ?uri .
}

Using entities:
Rotterdam, also known as R'dam, Roffa, Rotjeknor (wd:Q34370): city in South Holland, the Netherlands

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 3:
Question:
Which countries are connected by the Rhine?

SPARQL:
SELECT DISTINCT ?uri ?x ?y WHERE {
  wd:Q584 wdt:P17 ?uri .
  ?uri wdt:P31 wd:Q6256 .
}

Using entities:
Rhine (wd:Q584): river in Western Europe to the North Sea
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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

[Assistant]
The question is about the Italian national soccer team and how many times it won the FIFA World Cup.

Step 1: Identify the entity for the Italian national soccer team.
Step 2: Identify the property or event related to winning the FIFA World Cup.
Step 3: Count the number of times the Italian national soccer team has won the FIFA World Cup.

I will start by searching for the entity "Italian national soccer team" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Italy men's national association football team, also known as Team of Italy, The Azzurri, Italy NT, Italy national team, Italy national football team (wd:Q676899): men's national association football team representing Italy
2. national association football team, also known as national football team, national soccer team (wd:Q6979593): association football team that represents a country in international competitions
3. France men's national association football team, also known as France, France men's national football team, France national association football team, France national football team, France national soccer team (wd:Q47774): national association football team representing France
4. England men's national association football team, also known as England, Three Lions, England national soccer team, England national football team, England national association football team (wd:Q47762): men's national association football team representing England
5. Argentina men's national association football team, also known as Argentina men's national football team, Argentina men's national soccer team, Argentina national association football team, Argentina national football team, Argentina national soccer team (wd:Q79800): men's national association football team representing Argentina
6. Russia men's national football team, also known as Russia national football team, Russian national soccer team, Russia national soccer team, Russian national football team (wd:Q726080): men's national football team representing Russia
7. United States men's national soccer team, also known as US national soccer team, USMNT, US men's national soccer team, USA national team, USA national soccer team (wd:Q164134): men's national association football (soccer) team representing the USA
8. Denmark men's national football team, also known as Danish national football selection, Denmark soccer team, Denmark national soccer team, Denmark national selection team, Denmark national football team (wd:Q131785): men's national association football team representing Denmark
9. Australia men's national soccer team, also known as Australia men's national football team, Australia national football team, Australia national soccer team, Socceroos (wd:Q268208): men's national association football team representing Australia
10. Chile men's national football team, also known as Bicampeon, Chilean national football team, Chilean national soccer team, Chile national football team, Chile national soccer team (wd:Q172025): men's national association football team representing Chile

[Assistant]
The entity for the Italian national soccer team is "Italy men's national association football team" with the identifier wd:Q676899.

Next, I need to find the property or event related to winning the FIFA World Cup. I will search for properties related to "FIFA World Cup" or "win" in the context of the Italian national soccer team.

[Tool]
Top 10 property alternatives:
1. 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
2. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
3. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as wdt/p): country a person or a team represents when playing a sport, country
4. FIFA country code (wd:P3441 as wdt/p): three-letter country code assigned by FIFA
5. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. competition won, also known as won event, won, winner of, victory (wd:P2522 as wdt/p): competition or sports event won by the subject, participant in
7. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt/p): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
8. UEFA team ID, also known as UEFA club ID (wd:P7361 as wdt/p): identifier for a association football (soccer) team in the UEFA database
9. team captain, also known as captain, sports team captain (wd:P634 as wdt/p): captain of this sports team
10. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt/p): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person

No other items found

[Assistant]
The property "competition won" (wdt:P2522) seems to be the most relevant to find the competitions or sports events won by the Italian national soccer team.

Next, I will find the entity for the "FIFA World Cup" to filter the competitions won by the Italian national soccer team to only those that are FIFA World Cup wins.

[Tool]
Top 10 entity alternatives:
1. FIFA World Cup, also known as World Cup, The World Cup, Soccer World Cup, FWC, FIFA World Cup of Football (wd:Q19317): international association football competition contested by the senior men's national teams
2. FIFA World Cup (wd:Q864001): video game series
3. North Korea at the FIFA World Cup, also known as FIFA World Cup., Korea DPR at the FIFA World Cup (wd:Q6431616): participation of North Korea's national football team in the FIFA World Cup
4. 2018 FIFA World Cup, also known as FIFA 2018, FIFA World Cup 2018, World Cup 2018, World Cup 2018 in Russia, 2018 World Cup (wd:Q170645): 21st FIFA World Cup, held in Russia
5. 2014 FIFA World Cup, also known as FIFA 2014, 20th FIFA World Cup, 2014 FIFA World Cup Brasil, 2014 FIFA World Cup Brazil (wd:Q79859): 20th FIFA World Cup, held in Brazil
6. 2022 FIFA World Cup, also known as Qatar 2022, FIFA 2022, 2022 World Cup, FIFA world cup 2022 (wd:Q284163): 22nd FIFA World Cup
7. 2010 FIFA World Cup, also known as 2010 FIFA World Cup South Africa, FIFA 2010, FIFA World Cup 2010 (wd:Q176883): 19th FIFA World Cup, held in South Africa
8. 2006 FIFA World Cup, also known as 2006 World Cup, FIFA 2006 (wd:Q37285): 18th FIFA World Cup, held in Germany
9. 2002 FIFA World Cup, also known as 2002 FIFA World Cup Korea/Japan, FIFA 2002 (wd:Q47735): 17th FIFA World Cup, held in South Korea and Japan
10. 1930 FIFA World Cup (wd:Q48432): 1st FIFA World Cup, held in Uruguay

[Assistant]
The entity for the FIFA World Cup is wd:Q19317.

Now, I will write a SPARQL query to count how many times the Italy men's national association football team (wd:Q676899) has won the FIFA World Cup (wd:Q19317) using the property "competition won" (wdt:P2522).

[Tool]
Got 1 row and 1 column:
| winCount    |
| ----------- |
| 0 (xsd:int) |

[Assistant]
The query returned 0, which means the property "competition won" (wdt:P2522) with instance of FIFA World Cup (wd:Q19317) did not directly yield the wins for the Italian national soccer team.

I will try another approach. I will check the property "award received" (wdt:P166) for the Italy men's national association football team to see if the FIFA World Cup wins are recorded as awards.

[Tool] Got no rows and 1 columns

[Assistant]
There are no direct awards of type FIFA World Cup (wd:Q19317) for the Italian national soccer team.

I will try to find all competitions won by the Italian national soccer team and then check if any of them are instances of FIFA World Cup or subclasses of it. This might help to identify the correct property or entity for the FIFA World Cup wins.

[Tool]
Got 8 rows and 2 columns:
| competition                                                            | competitionLabel                                             |
| ---------------------------------------------------------------------- | ------------------------------------------------------------ |
| 1938 FIFA World Cup (wd:Q131591)                                       | 1938 FIFA World Cup (en)                                     |
| 1934 FIFA World Cup (wd:Q1477177)                                      | 1934 FIFA World Cup (en)                                     |
| 1968 UEFA European Championship (wd:Q182201)                           | 1968 UEFA European Championship (en)                         |
| 2006 FIFA World Cup (wd:Q37285)                                        | 2006 FIFA World Cup (en)                                     |
| UEFA Euro 2020 (wd:Q373501)                                            | UEFA Euro 2020 (en)                                          |
| Scania 100 Tournament (wd:Q3994651)                                    | Scania 100 Tournament (en)                                   |
| 1982 FIFA World Cup (wd:Q46934)                                        | 1982 FIFA World Cup (en)                                     |
| football at the 1936 Summer Olympics – men's tournament (wd:Q77316211) | football at the 1936 Summer Olympics – men's tournament (en) |

[Assistant]
The Italian national soccer team has won the following FIFA World Cups:
- 1934 FIFA World Cup (wd:Q1477177)
- 1938 FIFA World Cup (wd:Q131591)
- 1982 FIFA World Cup (wd:Q46934)
- 2006 FIFA World Cup (wd:Q37285)

There are 4 FIFA World Cup wins in total.

I will now finalize the answer with this information.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query returned 0 wins, which is incorrect because Italy has won the FIFA World Cup 4 times. The problem is that the property wdt:P2522 (competition won) used in the query might not be the correct property to find FIFA World Cup wins for the Italian national soccer team. Instead, the query should look for instances where the Italian national team is the winner of the FIFA World Cup events. A better approach is to find FIFA World Cup events (instances of wd:Q19317) where the winner (wdt:P1346) is Italy (wd:Q676899). The query should count such events. Also, ensure that the query returns the count of such events correctly. Please revise the query accordingly.

[Assistant]
Thank you for the feedback. I understand that the property "competition won" (wdt:P2522) might not be the correct property to find FIFA World Cup wins for the Italian national soccer team. Instead, I should look for FIFA World Cup events (instances of wd:Q19317) where the winner (wdt:P1346) is Italy (wd:Q676899).

I will revise the query to count the number of FIFA World Cup events where Italy is the winner.

[Tool]
Got 1 row and 1 column:
| winCount    |
| ----------- |
| 0 (xsd:int) |

[Assistant]
The query returned 0 wins, which is unexpected because Italy has won the FIFA World Cup 4 times. It might be that the property "winner" (wdt:P1346) is not used for the FIFA World Cup events or the data is structured differently.

I will try to find the winners of some known FIFA World Cup events to understand how the winners are represented. I will check the winner of the 2006 FIFA World Cup (wd:Q37285) as an example.

[Tool]
Got 1 row and 1 column:
| winner                                                      |
| ----------------------------------------------------------- |
| Italy men's national association football team (wd:Q676899) |

[Assistant]
The 2006 FIFA World Cup (wd:Q37285) has the winner property (wdt:P1346) set to the Italy men's national association football team (wd:Q676899).

This confirms that the property and entity are correct.

I will now try to find all FIFA World Cup events (instances of wd:Q19317) and their winners to see if the data is complete for other years as well.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the property "winner" (wdt:P1346) is not consistently used for all FIFA World Cup events, which is why the query returned no results for other years.

Given this inconsistency, I will revert to the previous approach where the Italian national soccer team has the property "competition won" (wdt:P2522) with specific FIFA World Cup events as values. I will count those events that are instances of the FIFA World Cup (wd:Q19317).

I will refine the query to count the number of competitions won by Italy that are instances of FIFA World Cup or its subclasses.

[Tool]
Got 1 row and 1 column:
| winCount    |
| ----------- |
| 0 (xsd:int) |

[Assistant]
The refined query still returns 0, which is unexpected.

Since the direct property approach is not yielding results, I will try a different approach: I will list all competitions won by the Italian national soccer team and check their labels to identify which ones are FIFA World Cup wins. Then I will count those manually in the query.

I already have the list of competitions won by Italy from a previous query. I will now filter those competitions by their labels containing "FIFA World Cup" and count them.

[Tool]
Got 1 row and 1 column:
| winCount    |
| ----------- |
| 4 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of FIFA World Cup competitions won by the Italian national soccer team (wd:Q676899) using the property 'competition won' (wdt:P2522). It filters the competitions by checking that their English label contains 'fifa world cup', ensuring the count is specific to the FIFA World Cup. The result of 4 matches the known fact that Italy has won the FIFA World Cup four times. The query adheres to the rules by returning the count directly and does not perform any post-processing outside SPARQL. Therefore, the answer and query are correct and complete.


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

Yes, Python is a kind of programming language.

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

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

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

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

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

[User] Is Python a kind of Programming languages?

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

[Tool]
Example 1:
Question:
Who developed Minecraft?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q49740 wdt:P178 ?uri .
}

Using entities:
Minecraft, also known as MC, Mine Craft, MineCraft (wd:Q49740): 2011 video game

Using properties:
developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as wdt): organization or person that developed the item, creator

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

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

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

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

Example 3:
Question:
What is the largest city in Australia?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q515 ; wdt:P17 wd:Q408 ; wdt:P1082 ?population .
}
ORDER BY DESC ( ?population )
LIMIT 1

Using entities:
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania
city, also known as cities (wd:Q515): large human settlement

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
The question is "Is Python a kind of Programming languages?" We need to check if Python is an instance or subclass of programming languages.

Step 1: Identify the entity for Python.
Step 2: Identify the entity for programming languages.
Step 3: Check if Python is an instance of or subclass of programming languages.

I will start by searching for the entity "Python" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Python, also known as Python (software), Python (scripting language), Python Programming Language, Python (Programming Language), Python (computer language) (wd:Q28865): general-purpose programming language
2. Python, also known as Piton (wd:Q271218): genus of reptiles
3. Python (wd:Q15721): earth-dragon of Delphi
4. Python (wd:Q15721): earth-dragon of Delphi
5. CPython, also known as Python (wd:Q599384): Python reference implementation
6. Python, also known as Derby, Python missile, RAFAEL Python (wd:Q15728): 1978 air-to-air missile family by RAFAEL
7. Peithon, also known as Python (wd:Q1249144): Ancient Macedonian general, military leader, satrap
8. Python, also known as Python II (wd:Q4363952): ancient peastan Greek vase-painter of red-figure style, red-figure vase painter, Paestan vase-painter, painter
9. Python (wd:Q3411448): 2000 film directed by Richard Clabaugh
10. Python, also known as Peithon (wd:Q18691580): ancient Attic-Greek potter, Attic potter, ceramicist

[Assistant] The entity for Python as a programming language is wd:Q28865. Next, I will search for the entity for programming languages.

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

[Assistant] The entity for programming language is wd:Q9143. Now I will check if Python (wd:Q28865) is an instance of or subclass of programming language (wd:Q9143).

[Tool] True

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that Python (wd:Q28865) is an instance of a programming language (wd:Q9143) by using the ASK query with the property path wdt:P31/wdt:P279* to check if Python is an instance of or subclass of programming languages. The query is well-formed, uses appropriate properties, and the answer 'Yes' is accurate based on the query result. No further refinement is needed.


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

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 https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

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

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

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

[User] Do more than 100000000 people speak Japanese?

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

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

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

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

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

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

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

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

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

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

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

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

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

[Assistant] The examples show how to query for numbers related to entities and how to filter by a threshold. Now I need to identify the entity for the Japanese language and the property for the number of speakers. Then I can build a query to check if the number of speakers is more than 100,000,000. I will start by searching for the entity "Japanese language".

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

[Assistant] The entity for the Japanese language is wd:Q5287. Now I need to find the property that represents the number of speakers of a language. I will search for properties related to "number of speakers" or "speakers" for this entity.

[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 wdt/p): number of people who use a language
2. indigenous to, also known as native to, originating from, spoken by (wd:P2341 as wdt/p): place or ethnic group where a language, art genre, cultural trad...biological species or variety is found (or was originally found)
3. audio, also known as audio file, audio recording, audio sample, recording, song (wd:P51 as wdt/p): relevant sound. If available, use a more specific property. Samples: "spoken text audio" (P989), "pronunciation audio" (P443)
4. language regulatory body, also known as language authority, regulatory body (wd:P1018 as wdt/p): regulatory body of a language
5. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as wdt/p): language status identifier by Ethnologue.com using EGIDS scale
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
7. ABS ASCL 2011 code, also known as 1267.0 Australian Standard Class... Languages, Second Edition, 2011, ASCL 2011 code, Australian Standard Classificati... Languages, Second Edition, 2011 (wd:P1251 as wdt/p): Numerical language identifier in the Australian Standard Classification of Languages regulated by Australian Bureau of Statistics
8. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
9. FAST ID, also known as Faceted Application of Subject Terminology ID, FAST subject heading, fst, worldcat.org/fast (wd:P2163 as wdt/wdtn/p): authority control identifier in WorldCat's “FAST Linked Data” authority file
10. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name

No other items found

[Assistant] The property for the number of speakers of a language is wd:P1098. Now I will write a SPARQL query to check if the number of speakers of Japanese (wd:Q5287) is more than 100,000,000.

[Tool] True

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly checks if the number of speakers of Japanese (wd:Q5287) is greater than 100,000,000 using the property number of speakers (wdt:P1098). The query is an ASK query, which is appropriate for a yes/no question. The execution result is True, which matches the provided answer. The query follows the rules by returning a boolean and uses the correct identifiers. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?castMember ?castMemberLabel ?birthDate WHERE {
  VALUES ?castMember {
    wd:Q29452671 wd:Q44870529 wd:Q49729241 wd:Q50377216 wd:Q50379405 wd:Q50379407
  }
  ?castMember wdt:P569 ?birthDate .
  OPTIONAL {
    ?castMember rdfs:label ?castMemberLabel FILTER ( LANG( ?castMemberLabel ) = "en" )
  }
}
ORDER BY ?birthDate
LIMIT 1

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[Assistant]
To answer the question "Who is the oldest cast member of the Netflix show 'Queer Eye'?", I need to identify the entity for the show "Queer Eye" and then find its cast members. After that, I will retrieve the birth dates of the cast members to determine who is the oldest.

Step 1: Search for the entity "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).

Step 2: Find the cast members of this show. I will look for the property that links the show to its cast members.

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

No other items found

[Assistant]
The property "cast member" (wdt:P161) is used to link the show to its cast members.

Step 3: Retrieve the cast members of the show "Queer Eye" (wd:Q48817408) using the property wdt:P161.

[Tool]
Got 6 rows and 2 columns:
| castMember                       | castMemberLabel        |
| -------------------------------- | ---------------------- |
| Jeremiah Brent (wd:Q29452671)    | Jeremiah Brent (en)    |
| Karamo Brown (wd:Q44870529)      | Karamo Brown (en)      |
| Bobby Berk (wd:Q49729241)        | Bobby Berk (en)        |
| Antoni Porowski (wd:Q50377216)   | Antoni Porowski (en)   |
| Jonathan Van Ness (wd:Q50379405) | Jonathan Van Ness (en) |
| Tan France (wd:Q50379407)        | Tan France (en)        |

[Assistant]
I have found the cast members of the Netflix show "Queer Eye": Jeremiah Brent, Karamo Brown, Bobby Berk, Antoni Porowski, Jonathan Van Ness, and Tan France.

Step 4: Now I will retrieve the birth dates of these cast members to determine who is the oldest.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the birth dates of all main cast members of the Netflix show "Queer Eye" and orders them by birth date ascending, returning the oldest cast member. The query uses the correct entities and properties, and the result correctly identifies Karamo Brown as the oldest cast member born on November 2, 1980. The answer is accurate and complete based on the data from Wikidata. No further refinement is needed.


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

The magazine in which Hunter x Hunter is published is Weekly Shōnen Jump. It was established in the year 1968.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[Assistant]
The question is about the magazine in which "Hunter x Hunter" is published and the establishment date of that magazine.

Step 1: Identify the entity "Hunter x Hunter" in Wikidata.
Step 2: Find the property that links "Hunter x Hunter" to the magazine it is published in.
Step 3: Find the establishment date of that magazine.

I will start by searching for the entity "Hunter x Hunter" in Wikidata.

[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 entity "Hunter × Hunter" as a Japanese manga series is identified as wd:Q696071. Next, I will find the property that links this manga series to the magazine it is published in. I will search for properties of the entity "Hunter × Hunter" related to publication or magazine.

[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) seems to be the correct property that links the manga series to the magazine it is published in. I will now query the magazine in which "Hunter × Hunter" is published using this property.

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

[Assistant] The magazine in which "Hunter × Hunter" is published is "Weekly Shōnen Jump" (wd:Q220015). Now, I will find the establishment date of this magazine. I will search for properties of the magazine "Weekly Shōnen Jump" related to establishment or inception.

[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 the relevant property for the establishment date of the magazine. I will now query the inception date of the magazine "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 (Weekly Shōnen Jump) and retrieves its inception date (1968). The query uses appropriate properties (P1433 for published in and P571 for inception) and returns the magazine's identifier, label, and inception date. The answer is accurate and complete based on the data retrieved. No further refinement is necessary.